[Ifeffit] Different R-factor values
Hello List, I know that Horae is no longer supported but I had quick question about the R-factor. I search the mailing list and found this post from 2006 concerning different R-factors in the fit log I have a question about Artemis log file. I noticed that two r-factors are reported in the log file. One is in the fifth line and it is called 'R-factor' and the other one is under the data set fitting conditions and it is called 'r-factor for this data set'. They have in general different values. What does it mean? Which is the difference between the two? It probably means that I am calculating something wrongly. Here's the concept. If you do a multiple data set fit and you have some value of R-factor, you would like to know how that misfit is partitioned among the data sets. That is, you'd like to know if one set is contributing to the misfit for significantly than the others. When Ifeffit computes the R-factor, it is for the entire fit. My idea in Artemis was to use the formula for R factor from page 18 of http://cars9.uchicago.edu/~newville/feffit/feffit.ps <http://cars9.uchicago.edu/%7Enewville/feffit/feffit.ps> on each data set in a multiple data set fit and report that in the log file. At some point, I must have convinced myself that I was doing the calulcation in Artemis identically to how it is done in Ifeffit. If you are seeing different values, it would seem I was mistaken. I'll make an entry in my to do list to look into that. I am reviewing some older analysis projects from artemis and just wanted to know which R-factor more accurately describes the misfit? I suspect the average over the k weights values since this was adopted in Demeter? Thanks, Chris Patridge -- Christopher J. Patridge, PhD NRC Post Doctoral Research Associate Naval Research Laboratory Washington, DC 20375 Cell: 315-529-0501 Project title : Fitting Cell_3_2_5V.003.chi Comment : Fit #1 Prepared by : Contact : Started : 11:07:39 on 23 February, 2011 This fit at : 17:46:41 on 8 November, 2011 Environment : Artemis 0.8.012 using Windows Vista, perl 5.008008, Tk 804.027, and Ifeffit 1.2.11 Data sets : "Fe2_2_5V.021.chi" Fit label : fit 5 Figure of merit : 5 Independent points = 4.502929688 Number of variables = 1.0 Chi-square =9463.223505940 Reduced Chi-square =2701.516830243 R-factor= 0.011247229 Measurement uncertainty (k) = 0.000419876 Measurement uncertainty (R) = 0.000780899 Number of data sets = 1.0 k-range = 3.000 - 11.000 dk = 1.000 k-window = hanning k-weight= 1,2,3 R-range = 1.335 - 2.243 dR = 0.000 R-window= hanning fitting space = R background function = none phase correction= none R-factor for this data set = 0.05390 R-factor with k-weight=1 for this data set = 0.01127 R-factor with k-weight=2 for this data set = 0.02877 R-factor with k-weight=3 for this data set = 0.12168 ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
[Ifeffit] R-factor uncertainty
Dear all, I have a question about the R factor: how can I decide if the difference between the R factors of 2 fits is statistically significant, i.e, how can I calculate the uncertainty which has to be associated to the R factor? B.R., Lisa ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
Re: [Ifeffit] Different R-factor values
Chris et al, Sorry I didn't pipe up earlier. I haven't had a good chance to sit down and follow this discussion until this afternoon. I'll start with the practical issue. Recently someone requested per-data-set R factors in Artemis. Being a perfectly fine request, I sat down to implement it. Since fits in Artemis are usually done with multiple k-weights, it wasn't clear to me how to display the information in the clearest manner. The "overall" R factor, the one that Ifeffit reports after the fit finishes, includes all the data and all the k-weights used in the fit. That is certainly a useful number in that it summarizes the closeness of the fit in the aggregate. As long as I was breaking down the R-factors by data set, I figured it would be useful to do so by k-weight also. I could imagine a scenario where knowing how a particular data set and a particular k-weight contributed to the overall closeness of the fit. That should explain the why of what you find in Artemis' log file. My intent is to use the same formula for R-factor as in the Ifeffit reference manual. If you do a single data set, single k-weight fit, theoverall R-factor and the per data set R-factor at the k-weight (all three are reported regardless) should be the same. It is possible that is not well enought tested. Matt's point about Larch being the superior tool for user-specified R-factors is certainly true, although few GUI users would avail themselves of that. If some R-factor other than one reported by Ifeffit (or, soon, the one reported by default by Larch) is needed, that would be a legitamate request. If something sophisticated or flexible is needed, that too can be put into the GUI. As for the actual question -- how to "decide" between the R-factors -- well, my take is that that's not a well posed question. The R factor is not reduced chi-square. It does not measure *goodness*, it only measures *closeness* of fit. The term "goodness" means something in a statistical context. An R-factor is some kind of percentage misfit without any consideration of how the information content of the actual data ensemble was used. In short, the R-factor is a numerical value expressing how closely the red line overplots the blue line in the plot made after Artemis finishes her fit. Thus, the overall R-factor expresses how closely all the red lines together overplot all the blue lines. The R-factors broken out by data set and k-weight express how closely a particular red line overplots a particular blue line. HTH, B On Friday, January 25, 2013 01:11:22 PM Christopher Patridge wrote: > Thank you for the discussion Matt and Jason, > > My main objective was to decide between the two different reported > R-factors in some older Artemis fit file logs. I suspect that the > analysis was prematurely completed because the user found small R-factor > values printed out along with the other fit statistics near the > beginning of the fit log. Scrolling down the log file to the area which > gives; > > R-factor for this data set = ? > k1,k2,k3 weightings R-factors = ? > > This R-factor is the average R-factor of the k-weights and much larger > say, 0.01 above vs. 0.07-0.08 making a typical "good fit" to a single > data set into a rather questionable one. > > Looking at more current fit logs from Demeter (attached, just a quick > example), the R-factor which is printed near the beginning of the fit > file is equal to the average R-factor for the k-weightings. Therefore > the value found in the earlier Artemis file logs must have been faulty > or buggy as was said so one should not rely on that value to evaluate > the fits. Sorry for any confusion but this is all in the name of > weeding out good/bad analysis > > Thanks again, > > Chris > > > Christopher J. Patridge, PhD > NRC Post Doctoral Research Associate > Naval Research Laboratory > Washington, DC 20375 > Cell: 315-529-0501 > > On 1/25/2013 12:04 PM, Matt Newville wrote: > > Hi Jason, Chris, > > > > On Fri, Jan 25, 2013 at 10:01 AM, Jason Gaudet wrote: > >> Hi Chris, > >> > >> Might be helpful also to link to the archived thread you're talking > >> about. > >> > >> http://millenia.cars.aps.anl.gov/pipermail/ifeffit/2006-June/007048.html > >> > >> Bruce might have to correct me on this, but if I remember right there > >> were > >> individual-data-set R-factor and chi-square calculations at some point, > >> which come not from IFEFFIT but from Bruce's own post-fit calculations, > >> and > >> these eventually were found to be pretty buggy and were dropped. > >> > >> I don't understand
Re: [Ifeffit] R-factor uncertainty
Hi Lisa, At 07:23 AM 1/5/2007, you wrote: I have a question about the R factor: how can I decide if the difference between the R factors of 2 fits is statistically significant, i.e, how can I calculate the uncertainty which has to be associated to the R factor? As I understand it, you can't. The R-factor is not a proper statistical measure, as it doesn't incorporate any measure of data quality. That's the great weakness of this measure of quality-of-fit. It is also its strength, as estimating the uncertainty in EXAFS data is notoriously problematic. The complementary statistic is reduced chi-square. It does incorporate a measure of data quality. By default, ifeffit uses noise from high in the FT to estimate this. That's a reasonable idea, but can be problematic. It has been shown (by Matt and/or Shelly, as I recall), that there may in some cases be signal in the part of the FT ifeffit is using to estimate noise. There are also cases where the noise may not be "white," that is, the noise high in the FT may be a poor estimate of the noise low in the FT. Ifeffit does allow you to specify a value of the measurement uncertainty instead, so if you think you have a way of doing this, go ahead. What does all this mean in practice? It means, in my opinion, that the actual =value= of the reduced chi-square statistic is usually meaningless, unless you have a good way of coming up with the measurement uncertainty (for example, your sample may be so dilute that errors are dominated by counting statistics). But reduced chi-square is a great statistic for comparing two fits to a given set of data, particularly if the k-range, k-weighting, and k-window are the same for the two fits. For example, you can apply statistical tests of significance, if you'd like. The R-factor then provides the reality check that the fit is "good" at all. The R-factor isn't doing anything other than what you can see by looking at a graph, but is a nice shorthand for tables showing the results of many fits and similar applications. If there's a big R-factor (say, 0.20), the question of statistical significance isn't necessary to tell you that you haven't got a conclusive positive result: maybe the R-factor is big because the fitting model is lousy, or maybe it's big because the data quality is lousy, but either way the fit shouldn't be trusted. I'd also add that your eye tells you considerably more than the R-factor, because you can tell the character of the mismatch. Is it in the high part of the FT, low, or evenly throughout? Is the miss primarily in amplitude, or phase? I often find I choose a fit with an R-factor of 0.03 over one with 0.01, if, for example, the 0.03 reproduces qualitatively all the features in the data but has small errors in the amplitude of the peaks, while the 0.01 fits the first part of the spectrum perfectly but misses some peak altogether. Hope that helps... --Scott Calvin Sarah Lawrence College ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
[Ifeffit] r-factor
Hi Everyone, I have a question about Artemis log file. I noticed that two r-factors are reported in the log file. One is in the fifth line and it is called 'R-factor' and the other one is under the data set fitting conditions and it is called 'r-factor for this data set'. They have in general different values. What does it mean? Which is the difference between the two? Lisa ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
[Ifeffit] Calculation of NSS and R-factor
Good afternoon, Could you please tell me what is the difference between the calculation of the R-factor and the NSS ? I found that R-factor is equal to : sum((data - fit)^2)/sum(data^2) and NSS = sum((data - fit)^2)/sum(data^2)*100 But when I compare the R-factor obtained by Athena and the NSS divided by 100 (calculated by myself) I didn't find the same results. Did I make a mistake somewhere. Thank you for your answer. Kind regards Marine Albertelli PhD student IPREM 2 av du Président Pierre Angot 64000 Pau FRANCE --- L'absence de virus dans ce courrier électronique a été vérifiée par le logiciel antivirus Avast. https://www.avast.com/antivirus ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit Unsubscribe: http://millenia.cars.aps.anl.gov/mailman/options/ifeffit
[Ifeffit] Fwd: Re: r-factor
On Friday 23 June 2006 05:01, you wrote: > I have a question about Artemis log file. I noticed that two r-factors are > reported in the log file. One is in the fifth line and it is called > 'R-factor' and the other one is under the data set fitting conditions and > it is called 'r-factor for this data set'. They have in general different > values. What does it mean? Which is the difference between the two? It probably means that I am calculating something wrongly. Here's the concept. If you do a multiple data set fit and you have some value of R-factor, you would like to know how that misfit is partitioned among the data sets. That is, you'd like to know if one set is contributing to the misfit for significantly than the others. When Ifeffit computes the R-factor, it is for the entire fit. My idea in Artemis was to use the formula for R factor from page 18 of http://cars9.uchicago.edu/~newville/feffit/feffit.ps on each data set in a multiple data set fit and report that in the log file. At some point, I must have convinced myself that I was doing the calulcation in Artemis identically to how it is done in Ifeffit. If you are seeing different values, it would seem I was mistaken. I'll make an entry in my to do list to look into that. B -- Bruce Ravel -- [EMAIL PROTECTED] Molecular Environmental Science Group, Building 203, Room E-165 MRCAT, Sector 10, Advanced Photon Source, Building 433, Room B007 Argonne National Laboratory phone and voice mail: (1) 630 252 5033 Argonne IL 60439, USAfax: (1) 630 252 9793 My homepage:http://cars9.uchicago.edu/~ravel EXAFS software: http://cars9.uchicago.edu/~ravel/software/exafs/ ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
Re: [Ifeffit] Different R-factor values
Thank you for the discussion Matt and Jason, My main objective was to decide between the two different reported R-factors in some older Artemis fit file logs. I suspect that the analysis was prematurely completed because the user found small R-factor values printed out along with the other fit statistics near the beginning of the fit log. Scrolling down the log file to the area which gives; R-factor for this data set = ? k1,k2,k3 weightings R-factors = ? This R-factor is the average R-factor of the k-weights and much larger say, 0.01 above vs. 0.07-0.08 making a typical "good fit" to a single data set into a rather questionable one. Looking at more current fit logs from Demeter (attached, just a quick example), the R-factor which is printed near the beginning of the fit file is equal to the average R-factor for the k-weightings. Therefore the value found in the earlier Artemis file logs must have been faulty or buggy as was said so one should not rely on that value to evaluate the fits. Sorry for any confusion but this is all in the name of weeding out good/bad analysis Thanks again, Chris Christopher J. Patridge, PhD NRC Post Doctoral Research Associate Naval Research Laboratory Washington, DC 20375 Cell: 315-529-0501 On 1/25/2013 12:04 PM, Matt Newville wrote: Hi Jason, Chris, On Fri, Jan 25, 2013 at 10:01 AM, Jason Gaudet wrote: Hi Chris, Might be helpful also to link to the archived thread you're talking about. http://millenia.cars.aps.anl.gov/pipermail/ifeffit/2006-June/007048.html Bruce might have to correct me on this, but if I remember right there were individual-data-set R-factor and chi-square calculations at some point, which come not from IFEFFIT but from Bruce's own post-fit calculations, and these eventually were found to be pretty buggy and were dropped. I don't understand what "the average over the k weights" R factor is; analyzing the same data set with multiple k weights (which is pretty typical) still means a single fit result and a single statistical output in IFEFFIT, as far back as I can remember, anyhow. The discussion about multiple R-factors is for when you're simultaneously fitting multiple data sets (i.e. trying to fit a couple different data sets to some shared or partially shared set of guess variables). I think the overall residuals and chi-square are the more statistically meaningful values, as they are actually calculated by the same algorithm used to determine the guess variables - they're the quantities IFEFFIT is attempting to reduce. I don't believe I've reported the per-data-set residuals in my final results, as I only treated it as an internal check for myself. (It would be nice to have again, though...) -Jason I can understand the desire for "per data set" R-factors. I think there are a few reasons why this hasn't been done so far. First, The main purpose of chi-square and R-factor are to be simple, well-defined statistics that can be used to compare different fits. In the case of R-factor, the actual value can also be readily interpreted and so mapped to "that's a good fit" and "that's a poor fit" more easily (even if still imperfect). Second, it would be a slight technical challenge for Ifeffit to make these different statistics and decide what to call them. Third, this is really asking for information on different portions of the fit, and it's not necessarily obvious how to break the whole into parts. OK, for fitting multiple data sets, it might *seem* obvious how to break the whole. But, well, fitting with multiple k-weights *is* fitting different data. Also, multiple-data-set fits can mix fits in different fit spaces, with different k-weights, and so on. Should the chi-squared and R-factors be broken up for different k-weights too? Perhaps they should. You can different weights to different data sets in a fit, but how to best do this can quickly become a field of study on its own. I guess that's not a valid reason to not report these So, again, I think it's reasonable to ask for per-data-set and/or per-k-weight statistics, but not necessarily obvious what to report here. For example, you might also want to use other partial sums-of-squares (based on k- or R-range, for example) to see where a fit was better and worse.Of course, you can calculate any of the partial sums and R-factors yourself. This isn't so obvious with Artemis or DArtemis, but it is possible. It's much easier to do yourself and implement for others with larch than doing it in Ifeffit or Artemis. Patches welcome for this and/or any other advanced statistical analyses. Better visualizations of the fit and/or mis-fit might be useful to think about too. --Matt ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.
Re: [Ifeffit] Athena: the R factor for normalized mu(E)
Hi Jon Petter, On Tue, Jul 12, 2022 at 12:46 AM Jon-Petter Gustafsson < jon-petter.gustafs...@slu.se> wrote: > Hello all, > > > > I have been a frequent user of Athena for many years, mostly for > interpreting P K-edge XANES spectra. Until last week I thought that the R > factor in Athena was always defined as: > > > > sum( [data_i – fit_i]^2 ) > > --- > >sum( data_i^2 ] > > > > This is also the definition given in the online manual, and it has been > stated by me and by other colleagues in a number of papers dealing with P > K-edge XANES. But well, this is not true when dealing with normalized XANES > spectra! I realized this when I played around with a number of my old LC > fits in Excel. While the chi-square value (or maybe more precisely, the sum > of squared residuals) was reproduced perfectly, I always got “R factors” > (i.e. with the above definition) between 2 and 3 times lower than what > Athena gives. After that I consulted the Demeter programming documentation ( > https://bruceravel.github.io/demeter/pods/Demeter/LCF.pm.html) to find > that, for normalized mu(E), “Demeter thus scales the R-factor to make it > somewhat closer to 10^-2”. However, the equation stated on this page > actually reproduces the R factor even more poorly, and therefore I won’t > reiterate it here. After inspecting the Perl code, and trying out > different alternatives in Excel, I now believe that the following equation > provides a more accurate definition of the R factor (correct me if I’m > wrong!): > > > > sum( [data_i – fit_i]^2 ) > > --- > > sum( [data_i – avg data]^2 ) > > > > where “avg data” is the arithmetic mean of the data in the LC fitting > range. It would be great if others could confirm this. As far as I > understand, this won’t affect the interpretations that any of us have made > over the years, it only affects the understanding of what the R factor > actually is… > Thanks, and yes, that does appear to be exactly what the Demeter code is doing. I never noticed that, or I guess it has honestly been a very long time since I used Athena for linear combination fitting. I'm not 100% sure why it would do that when fitting normalized mu(E), but not otherwise. I agree that it will not alter the actual interpretation of whether one fit is better than another. It might be that some sort of "remove the most obvious data trend" (often called "whitening") is a fine thing to do. FWIW, linear combination fitting in Larch reports an R-factor that does not subtract the average of the data in the denominator. Maybe it should? OTOH, one of the appealing features of the R factor is that it is meant to be really easy to understand and reproduced. Cheers, --Matt ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit Unsubscribe: http://millenia.cars.aps.anl.gov/mailman/options/ifeffit
[Ifeffit] Athena: the R factor for normalized mu(E)
Hello all, I have been a frequent user of Athena for many years, mostly for interpreting P K-edge XANES spectra. Until last week I thought that the R factor in Athena was always defined as: sum( [data_i - fit_i]^2 ) --- sum( data_i^2 ] This is also the definition given in the online manual, and it has been stated by me and by other colleagues in a number of papers dealing with P K-edge XANES. But well, this is not true when dealing with normalized XANES spectra! I realized this when I played around with a number of my old LC fits in Excel. While the chi-square value (or maybe more precisely, the sum of squared residuals) was reproduced perfectly, I always got "R factors" (i.e. with the above definition) between 2 and 3 times lower than what Athena gives. After that I consulted the Demeter programming documentation (https://bruceravel.github.io/demeter/pods/Demeter/LCF.pm.html) to find that, for normalized mu(E), "Demeter thus scales the R-factor to make it somewhat closer to 10^-2". However, the equation stated on this page actually reproduces the R factor even more poorly, and therefore I won't reiterate it here. After inspecting the Perl code, and trying out different alternatives in Excel, I now believe that the following equation provides a more accurate definition of the R factor (correct me if I'm wrong!): sum( [data_i - fit_i]^2 ) --- sum( [data_i - avg data]^2 ) where "avg data" is the arithmetic mean of the data in the LC fitting range. It would be great if others could confirm this. As far as I understand, this won't affect the interpretations that any of us have made over the years, it only affects the understanding of what the R factor actually is... Kind regards, Jon Petter Jon Petter Gustafsson, Professor in Soil Chemistry Department of Soil and Environment Swedish University of Agricultural Sciences (SLU) Box 7014 750 07 Uppsala, Sweden Phone: 018-671284; e-mail: jon-petter.gustafs...@slu.se<mailto:jon-petter.gustafs...@slu.se> --- N?r du skickar e-post till SLU s? inneb?r detta att SLU behandlar dina personuppgifter. F?r att l?sa mer om hur detta g?r till, klicka h?r <https://www.slu.se/om-slu/kontakta-slu/personuppgifter/> E-mailing SLU will result in SLU processing your personal data. For more information on how this is done, click here <https://www.slu.se/en/about-slu/contact-slu/personal-data/> ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit Unsubscribe: http://millenia.cars.aps.anl.gov/mailman/options/ifeffit
Re: [Ifeffit] Calculation of NSS and R-factor
Hello Marine, On Tue, May 16, 2017 at 4:59 AM, Marine Albertelli < marine.alberte...@univ-pau.fr> wrote: > Good afternoon, > > Could you please tell me what is the difference between the calculation of > the R-factor and the NSS ? > > I found that R-factor is equal to : sum((data - fit)^2)/sum(data^2) and > NSS = sum((data - fit)^2)/sum(data^2)*100 > > But when I compare the R-factor obtained by Athena and the NSS divided by > 100 (calculated by myself) I didn't find the same results. > > Did I make a mistake somewhere. > > Thank you for your answer. > > As you might imagine, it would be very difficult to answer a question about the comparison you made without seeing more details. Please post data (perhaps an Athena project file) and a detailed description of what you actually did, what result you got, and what result you expected to get. Cheers, --Matt ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit Unsubscribe: http://millenia.cars.aps.anl.gov/mailman/options/ifeffit
RE: [Ifeffit] R-factor uncertainty
Hi Lisa, In general the R-factor is good if it is less than a few percent. The value reported is 0.01 or 1% then the fit is satisfactory. Just as a note the R-factor is calculated over the entire data range given by rmin and rmax of the fit, so make sure that they are reasonable values. To compare two different models, use the reduced-chi-square (RCS) value. One standard deviation in the RCS value is SQRT(2/nu), where SQRT is square-root and nu is the number of independent points. If the first model has RCS1 and nu1 and the second model has RCS2 and nu2 then the second model is better than the first model if their difference (RCS1-RCS2) is greater than 2*SQRT((2*RCS1*RCS1)/nu1 + (2*RCS2*RCS2)/nu2)) which is twice the fluctuation of the difference. The number of independent points is equal to the number of data points minus the number of variables in the model. I do this kind of comparison in this paper: S.D. Kelly, K.M. Kemner, G.E. Fryxell, J. Liu, S.V. Mattigod, K.F. Ferris, "X-ray Absorption Fine-Structure Spectroscopy Study of the Interactions Between Contaminant Tetrahedral Anions and Self-Assembled Monolayers on Mesoporous Supports," The Journal of Physical Chemistry B 105 (27) 6337-6346, Aug 2001. The paper can be found here: http://www.mesg.anl.gov/sdkpublist.html. Cheers, Shelly --- Shelly Kelly Argonne National Laboratory Bldg 203, RM E113 9700 S. Cass Ave Argonne, IL 60439 Molecular Environmental Science Group www.mesg.anl.gov [EMAIL PROTECTED] phone: 630-252-7376 > -Original Message- > From: [EMAIL PROTECTED] [mailto:ifeffit- > [EMAIL PROTECTED] On Behalf Of Lisa Giachini > Sent: Friday, January 05, 2007 6:23 AM > To: XAFS Analysis using Ifeffit; FEFF Users > Cc: XAFS Analysis using Ifeffit > Subject: [Ifeffit] R-factor uncertainty > > > > Dear all, > > I have a question about the R factor: how can I decide if the difference > between the R factors of 2 fits is statistically significant, i.e, how can > I calculate the uncertainty which has to be associated to the R factor? > > B.R., > > Lisa > > ___ > Ifeffit mailing list > Ifeffit@millenia.cars.aps.anl.gov > http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
Re: [Ifeffit] Consultation on Reduced Chi2
Jesus, On Mon, May 23, 2016 at 7:08 AM, Jesús Eduardo Vega Castillo < jeve...@gmail.com> wrote: > Dear list, > > I am back with a new consultation on EXAFS fitting within Artemis. > > I have made a fit and obtained a reduced Chi2 value of 391 and R-factor of > 0.014 using 9 variables. Then I have added two more paths increasing the > number of variables up to 12 and then I obtained a reduced Chi2 of 3039 and > R-factor of 0.007. > > I am a little surprised by the huge increase of reduced Chi2 while > R-factor decreases down to half. > > What could be the cause of this large increase? > Does it mean that it is not worth to add these new paths? > > Reduced chi-square is scaled by dividing by the number of free parameters, (Nidp - Nvarys). Increasing the Nvarys from 9 to 12 without also increasing Nidp (by adding data k or R range), could definitely make reduced chi-square increase even if the R-factor and chi-square decrease. One of the main uses of reduced chi-square is to determine if additional variables are improving the fit well enough to justify their inclusion in the model. --Matt ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit Unsubscribe: http://millenia.cars.aps.anl.gov/mailman/options/ifeffit
Re: [Ifeffit] Different R-factor values
Perhaps next time I'll notice the attachment ... I don't see that "r factor for k-weight=..." in my old projects; I'm not sure if I just never used that version? I checked some Artemis 0.8.006 logfiles from 2009 and per-k-weight R-factors aren't in there, so that's a little weird. I'm still pretty sure, as you say, the overall R-factor is the statistically meaningful one. -Jason On Fri, Jan 25, 2013 at 11:01 AM, Jason Gaudet wrote: > Hi Chris, > > Might be helpful also to link to the archived thread you're talking about. > > http://millenia.cars.aps.anl.gov/pipermail/ifeffit/2006-June/007048.html > > Bruce might have to correct me on this, but if I remember right there were > individual-data-set R-factor and chi-square calculations at some point, > which come not from IFEFFIT but from Bruce's own post-fit calculations, and > these eventually were found to be pretty buggy and were dropped. > > I don't understand what "the average over the k weights" R factor is; > analyzing the same data set with multiple k weights (which is pretty > typical) still means a single fit result and a single statistical output in > IFEFFIT, as far back as I can remember, anyhow. The discussion about > multiple R-factors is for when you're simultaneously fitting multiple data > sets (i.e. trying to fit a couple different data sets to some shared or > partially shared set of guess variables). > > I think the overall residuals and chi-square are the more statistically > meaningful values, as they are actually calculated by the same algorithm > used to determine the guess variables - they're the quantities IFEFFIT is > attempting to reduce. I don't believe I've reported the per-data-set > residuals in my final results, as I only treated it as an internal check > for myself. (It would be nice to have again, though...) > > -Jason > > On Thu, Jan 24, 2013 at 10:12 AM, Christopher Patridge < > patri...@buffalo.edu> wrote: > >> I am reviewing some older analysis projects from artemis and just wanted >> to know which R-factor more accurately describes the misfit? I suspect the >> average over the k weights values since this was adopted in Demeter? >> >> Thanks, >> >> Chris Patridge >> >> -- >> >> Christopher J. Patridge, PhD >> NRC Post Doctoral Research Associate >> Naval Research Laboratory >> Washington, DC 20375 >> Cell: 315-529-0501 >> >> >> ___ >> Ifeffit mailing list >> Ifeffit@millenia.cars.aps.anl.gov >> http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit >> >> > ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
Re: [Ifeffit] Consultation on Reduced Chi2
Thank you very much Matt 2016-05-23 9:21 GMT-03:00 Matt Newville : > Jesus, > > > > On Mon, May 23, 2016 at 7:08 AM, Jesús Eduardo Vega Castillo < > jeve...@gmail.com> wrote: > >> Dear list, >> >> I am back with a new consultation on EXAFS fitting within Artemis. >> >> I have made a fit and obtained a reduced Chi2 value of 391 and R-factor >> of 0.014 using 9 variables. Then I have added two more paths increasing the >> number of variables up to 12 and then I obtained a reduced Chi2 of 3039 and >> R-factor of 0.007. >> >> I am a little surprised by the huge increase of reduced Chi2 while >> R-factor decreases down to half. >> >> What could be the cause of this large increase? >> Does it mean that it is not worth to add these new paths? >> >> > Reduced chi-square is scaled by dividing by the number of free parameters, > (Nidp - Nvarys). Increasing the Nvarys from 9 to 12 without also > increasing Nidp (by adding data k or R range), could definitely make > reduced chi-square increase even if the R-factor and chi-square decrease. > > One of the main uses of reduced chi-square is to determine if additional > variables are improving the fit well enough to justify their inclusion in > the model. > > --Matt > > ___ > Ifeffit mailing list > Ifeffit@millenia.cars.aps.anl.gov > http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit > Unsubscribe: http://millenia.cars.aps.anl.gov/mailman/options/ifeffit > > ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit Unsubscribe: http://millenia.cars.aps.anl.gov/mailman/options/ifeffit
Re: [Ifeffit] (no subject)
On Wednesday, March 13, 2013 08:24:41 PM davood dar wrote: > 1. *1*.What is the ideal value of R- factor for any fit. R-factor is a way of expressing percentage misfit. Smaller is generally better, although smaller is not better if other aspects of the fit are not defensible. For instance, if one of the fitting parameters is physically unreasonable, then getting a smaller R-factor is not so useful. R-factor is just one of the ways that the quality of the fit is evaluated. I discuss in some detail the statistical parameters reported by the software here: https://speakerdeck.com/bruceravel/advanced-topics-in-exafs-analysis > 2. *2. * Can we use (fit) the theoretical model generated from square > pyramidal structure to EXAFS data of octahedral structure by assigning > degeneracy of 2 for the apical atom. OR using octalhedral for square planar > by not using apical path Making clever use of Feff calculation on known structures to investigate unknown structures is something I talk about in https://speakerdeck.com/bruceravel/modeling-non-crystalline-samples Lots more information at http://xafs.org and at http://bruceravel.github.com/demeter/ B -- Bruce Ravel bra...@bnl.gov National Institute of Standards and Technology Synchrotron Methods Group at NSLS --- Beamlines U7A, X24A, X23A2 Building 535A Upton NY, 11973 Homepage:http://xafs.org/BruceRavel Software:https://github.com/bruceravel ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
[Ifeffit] Consultation on Reduced Chi2
Dear list, I am back with a new consultation on EXAFS fitting within Artemis. I have made a fit and obtained a reduced Chi2 value of 391 and R-factor of 0.014 using 9 variables. Then I have added two more paths increasing the number of variables up to 12 and then I obtained a reduced Chi2 of 3039 and R-factor of 0.007. I am a little surprised by the huge increase of reduced Chi2 while R-factor decreases down to half. What could be the cause of this large increase? Does it mean that it is not worth to add these new paths? As always, thank you in advance Yours, Jesús ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit Unsubscribe: http://millenia.cars.aps.anl.gov/mailman/options/ifeffit
Re: [Ifeffit] running ifeffit under 64-bit windows7
Hi Sameh, On Sat, Mar 10, 2012 at 8:17 AM, Sameh Ibrahim Ahmed wrote: > > Hi, > > I have used ARTEMIS to fit the EXAFS of a simple Cu foil with the two > diffrent machines, a 32 bit and 64 bit ones, both running widows7, 32 ans 64 > bit respectively. > The results obtained are slightly different, I have appended the message > with these results. the very low value of R-factor produced with the 64bit > system is difficult to interpret. the questions are; > 1- how to account for these differences? > 2- if I to publish something, which measure of the quality should I present? > and how can I interpret it? > > regards > Sameh > > > 32bit windows 7 > Independent points = 12.172851562 > Number of variables = 6.0 > Chi-square = 53.001967099 > Reduced Chi-square = 8.586301900 > R-factor= 0.000163791 !!! > Measurement uncertainty (k) = 0.000110566 > Measurement uncertainty (R) = 0.057163282 > Number of data sets = 1.0 > > Guess parameters +/- uncertainties (initial guess): > amp = 0.9907500 +/- 0.0312520(1.) > enot= 5.6814210 +/- 0.3815760(0.) > delr1 = 0.0016460 +/- 0.0033990(0.) > ss1 = 0.0099820 +/- 0.0004090(0.0030) > w1 3rd cumulant = 0.0001710 +/- 0.340(0.) > p1 4th cumulant = 0.240 +/- 0.070(0.) > > > 64bit windows 7 > Independent points = 12.172851562 > Number of variables = 6.00000 > Chi-square = 54.036163164 > Reduced Chi-square = 8.753841335 > R-factor= 0.309664502E-06 !!! > Measurement uncertainty (k) = 0.97377 > Measurement uncertainty (R) = 0.050344538 > Number of data sets = 1.0 > > Guess parameters +/- uncertainties (initial guess): > amp = 1.0029100 +/- 0.0296670(1.) > enot= 5.7522760 +/- 0.4614510(0.) > delr1 = 0.0024980 +/- 0.0040190(0.) > ss1 = 0.0101430 +/- 0.0003790(0.0030) > w1 3rd cumulant = 0.0001780 +/- 0.410 (0.) > p1 4th cumulant = 0.260 +/- 0.070(0.) > ==== > Except for R-factor, these differences are pretty small -- all parameters are well within the estimated error bars. I'm not sure why R-factor is different. I would say that there is essentially no difference in what to report the R factors are both small enough to mean "very good fit", and any difference between them would really only important when comparing two different fits -- in that case, just be consistent. But that's not to say that it's not worth trying to understand the difference but that might take a bit of investigative work. One thing I noticed in the projects you sent (only to me -- please use the mailing list!!) is that these fits use different versions of Athena and ifeffit: 32bit Win7: Artemis 0.8.012, ifeffit 1.2.11 64bin Win7: Artemis 0.8.014, ifeffit 1.2.11c Off hand, I don't know that either of these is actually significant. --Matt ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
Re: [Ifeffit] Fwd: Re: why ss_2 is negative?
Hi Hao, I haven't had time to look at your fits, but I have some generic responses to what you say below. It is typical of someone new to the field to chase r-factors. Don't do it! I could take any spectrum and any model and by floating enough variables, come up with a terrific looking r-factor...for a fit that's utter nonsense. At the risk of having another set of completely arbitrary criteria named after me , here's the guidelines I give undergraduates when I'm teaching the technique. (Note: these guidelines apply to decent-quality data. For cases like very dilute fluorescence, it's reasonable to expect statistical effects to inflate the R-factor a bit.) R-factor > 0.10: Serious problems with the fit. The underlying model may be incorrect. It's best at this stage to look at the spectrum for clues. Maybe the wiggles are qualitatively right, but shifted over or the wrong amplitude. Then the model may be OK, but things like the free parameters and constraints may need to be adjusted. On the other hand, the wiggles may be qualitatively wrong, in which case the underlying model must be seriously questioned. R-factor in the range 0.05 to 0.10: Underlying model may be correct, but there is likely some effect not being taken into account (for example: phase impurity, oversimplified sigma2 constraints, vacancies, etc., etc.). Alternatively, perhaps it's too wide a k-range, problems with background subtraction, or the like. I have occasionally published fits in this range, although always with an explanation of possible factors in the text of the article. R-factor in the range 0.02 to 0.05: Decently good match between fitted and actual spectra. There's still enough of a mismatch that, if the data is good quality, there are probably some issues with details of the model. At this point, R-factors are becoming less of a concern than the plausibility of the constraint scheme and the fitted parameters, the number of degrees of freedom, agreement with other source of information about the system, etc.. R-factor less than 0.02. Good match between fitted and actual spectra. Unless you're doing technical work on a very well-characterized sample (say, a piece of copper foil), there's no point in trying to reduce the R-factor any further. You're a lot better off with a constraint scheme that can be explained on physical grounds and an R-factor of 0.019, than, for example, introducing a parameter for the third cumulant of a fourth-nearest-neighbor in a metal to get an R-factor of 0.005. These are broad guidelines only; the R-factor has no meaning in a statistical sense, so what to expect is highly dependent on data quality. * * * OK--I've taken a very quick look at your fits to help answer your question about the k-weights. Your k-weight 2 and k-weight 3 fits are consistent, in that the error bars of corresponding parameters overlap. But the k-weight 2 fit has enormous uncertainties, and is thus pretty much useless. What good does it do you to find that n1 is 3.4 +/- 3.5? Presumably you knew that already. :) So in that sense the k-weight 3 fit is "better." But there are other problems: --the S02 is a bit high. Ideally it shouldn't be higher than 1.0. --You seem to be fitting too high an R-range. Going to 3 when your most distant path has an Reff of 2.4 is dangerous...depending on your substance there may be other stuff out there you're not accounting for. --The negative sigma2 that you're worried about is NOT a big problem, however. It is given as -0.003 +/- 0.008. So it could be positive according to the fitted results. --It looks like you set n2 to 0.175 based on some previous fit. Do you believe that's physically reasonable for your system? This business of running a fit, finding some parameters, and then running a fit on the same data fixing some parameters to values from a previous fit is at best dangerous, and at worst nonsense. That's different than the advice often given on this list, where you compare a fit with a parameter fixed to a suspected-prior-knowledge value to one where it is allowed to float. For example, saying "the chemists tell me this coordination number should be 6. I'll fix it at 6, and I'll let it float, and if the floated case doesn't seem better, I'll go back to fixing it at 6" is very different from "my first fit on this sample gave me a coordination number of 5.47 +/- 4.8. That's a big uncertainty, so I'll set the coordination number to 5.48 and proceed." Using the first procedure in a final, published fit is defensible, the second one is not. Hope that helps. --Scott Calvin Sarah Lawrence College At 01:48 PM 2/27/2007, you wrote: >I took your suggestion and have the amp and e0 the same for each path. In >addition, I fixed the number axial U-O as 2. For the equa
Re: [Ifeffit] Chi in arthemis
Dear Eugenio, > I see that the R-factor is pretty good, 1.74%, amp is high cause is > correlated with the coordination number and always have big errors., delr > has the error of the total distance, so it is ok, but ss and enot have a a > really big error, is this normal? What leads you to conclude that the uncertainty in delr (of ~0.016 Ang) is OK, but the uncertainty in ss (~0.0025 Ang^2) and enot (~2 eV) are really big? I don't know how to interpret the value for "amp" or assess why it would have a "big error" (is that a big error? how is "amp" used in your model?). Generally, for "decent data" and a good fit, R has uncertainty of 0.01 or 0.02 Ang, E0 has uncertainty of 0.5 to 1.0 eV, and the amplitude factors (N and sigma^2) are good to 10% or so. Without knowing more details, I'd say that your results fit within the "normal" range. Having a "reasonable R-factor" of a few percent misfit and a reduced chi-square of ~100 means the misfit is much larger than the estimated uncertainty in the data. This is not at all unusual. It does not necessarily mean (as Scott implies) that this is because the uncertainty in data is unreasonably low, but can also mean that there are systematic problems with the FEFF calculations that do not account for the data as accurately as it can be measured. For most "real" data, it is likely that both errors FEFF and a slightly low estimate for the uncertainty in the data contribute to making reduced chi-square much larger than 1. And, yes, the community-endorsed recommendation is to report either chi-square or reduced chi-square as well as an R-factor. I think some referees might find it a little deceptive to report R-factor because it is "acceptably small" but not reduced chi-square because it is "too big". --Matt On Tue, Aug 18, 2009 at 5:18 PM, Eugenio Otal wrote: > Hi Scott, > here I copy a part of the report: > > Independent points = 6.222656250 > Number of variables = 4.0 > Chi-square = 247.145092496 > Reduced Chi-square = 111.193574128 > R-factor = 0.017422216 > > Guess parameters +/- uncertainties (initial guess): > amp = 6.7815290 +/- 1.4687660 (1.) > enot = 2.2173620 +/- 2.1499920 (0.) > delr = 0.0514640 +/- 0.0163900 (0.) > ss = 0.0074020 +/- 0.0025220 (0.0030) > > I see that the R-factor is pretty good, 1.74%, amp is high cause is > correlated with the coordination number and always have big errors., delr > has the error of the total distance, so it is ok, but ss and enot have a a > really big error, is this normal? > Thanks, euG > > ___ > Ifeffit mailing list > Ifeffit@millenia.cars.aps.anl.gov > http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit > > ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
[Ifeffit] Per-data set R-factor
Dear iffefit users, I am using the latest version of Demeter/Artemis to fit some EXAFS data. I'm running Win 7 64. I found in Horae that when I fit multiple datasets it would output the R-factor for each dataset in the fit. I would really like these values in the newest version. I found on the todo list (https://github.com/bruceravel/demeter/blob/master/todo.org) [ ] per-data set R-factor reporting in log file is turned off. Is there a simple way to turn this "on"? If not I guess I can calculate it by hand from the Re/Im terms of the R space data and fit. To that end, if I have a few datasets it is tedious to export the data/fit files for each sample. Is there an automated way to export this data? Thanks very much, Lyle -- Lyle Gordon Department of Materials Science and Engineering Northwestern University 2220 Campus Drive Cook Hall 2036 Evanston, IL 60208 Tel: (847) 491-3584 Mobile: (847) 400-4071 http://lylegordon.ca ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
Re: [Ifeffit] Different R-factor values
Hi Chris, Might be helpful also to link to the archived thread you're talking about. http://millenia.cars.aps.anl.gov/pipermail/ifeffit/2006-June/007048.html Bruce might have to correct me on this, but if I remember right there were individual-data-set R-factor and chi-square calculations at some point, which come not from IFEFFIT but from Bruce's own post-fit calculations, and these eventually were found to be pretty buggy and were dropped. I don't understand what "the average over the k weights" R factor is; analyzing the same data set with multiple k weights (which is pretty typical) still means a single fit result and a single statistical output in IFEFFIT, as far back as I can remember, anyhow. The discussion about multiple R-factors is for when you're simultaneously fitting multiple data sets (i.e. trying to fit a couple different data sets to some shared or partially shared set of guess variables). I think the overall residuals and chi-square are the more statistically meaningful values, as they are actually calculated by the same algorithm used to determine the guess variables - they're the quantities IFEFFIT is attempting to reduce. I don't believe I've reported the per-data-set residuals in my final results, as I only treated it as an internal check for myself. (It would be nice to have again, though...) -Jason On Thu, Jan 24, 2013 at 10:12 AM, Christopher Patridge wrote: > I am reviewing some older analysis projects from artemis and just wanted > to know which R-factor more accurately describes the misfit? I suspect the > average over the k weights values since this was adopted in Demeter? > > Thanks, > > Chris Patridge > > -- > > Christopher J. Patridge, PhD > NRC Post Doctoral Research Associate > Naval Research Laboratory > Washington, DC 20375 > Cell: 315-529-0501 > > > ___ > Ifeffit mailing list > Ifeffit@millenia.cars.aps.anl.gov > http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit > > ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
Re: [Ifeffit] Find R-factor for linear combination sums?
Thanks, Matt, I'll give it a try. --Scott On Jan 8, 2012, at 10:06 PM, Matt Newville wrote: It should be possible to calculate an R-factor or chi-square statistics with a fairly simple ifeffit macro, using the functions vsum() (to sum an array) and npts(). ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
[Ifeffit] error
Hi all I fitted ZnMgO to know whether Mg is sited on Zn position. the method of fitting as following; 1st : to fit with some Mg located on Zn site. 2nd: to fit with some Mg which position is different from Zn cite The parameters for Mg like bonding length, disorder and others were set. When I was fitting, there are only 8 parameters in both two method. So that independent data point and variables are same. Both 1st and 2nd had same R-factor but reduced chi-square of 1st was lager than that of 2nd. It has been known that R-factor is independent of error( uncertainty in the measurement) but reduced chi-squrare is inverse proportional to error^2. So I think that same R-factor and different reduced chi-square for two method mean the fittings of two method are not different, but error used in reduced chi-square is different. I want to know how the error used in reduced chi-square is decided in FEFFIT code. ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
[Ifeffit] Query regarding error bars
Hi all, Could any tell me in a simple language about the error bars returned by the EXAFS fitting program? what do they exactly represent?How is it determined?How is the number of iterations decided.In addition to R-factor what are the other parameters which determines a good fit.For a R-factor ~0.001, if the value of chi2~10,000 and reduced chi2 ~ 500, can one consider the fit to be good even if one gets a good match to the experimental spectra. Bindu Dr.Bindu R. Visiting Fellow BG-37 DCMP&MS Tata Institute of Fundamental Research Homi Bhabha Road Colaba Mumbai-400 005 India Contact Number Lab- 022-2278 2256, 022-2278 2671 Mobile-919892536830 Add more friends to your messenger and enjoy! Go to http://messenger.yahoo.com/invite/___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
[Ifeffit] R quality factor in k space
Dear iffefit user, I found on a paper (E.A. Stern et al. /Physica B 208&209 (1995) 117 120) the definition of R quality factor as: R_factor ≡ < ∆chi(R space))> = √[ ∑ |chi_C(Ri) – chi_E(Ri)|2 / ∑( chi_E(Ri))2] > formula 3 Where Chi(Ri) is a complex function (imaginary and real part of the XAFS spectra in the R space), C concerns the calculated XAFS spectrum, while E refers to the experimental XAFS spectrum. In the case of a linear combination fitting on the k space performed by ATHENA, the <∆chi> needs a correction. Is it correct to write: R_factor ≡ < ∆chi(k space))> = √[ ∑ (chi_C(ki) – chi_E(ki))2 / ∑( chi_E(ki))2] ? Where Chi_C(ki) = x1*chi1(k)+x2*chi2(k) : chi1 and chi2 are the EXAFS functions of the two reference samples used for the linear combination procedure and x1, x2 (with 0___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
Re: [Ifeffit] Find R-factor for linear combination sums?
Hi Scott,
On Sat, Jan 7, 2012 at 12:42 PM, Scott Calvin wrote:
> Hi all,
>
> Is there a way to get Athena (or Ifeffit) to report an R-factor for a linear
> combination sum, as opposed to a fit? Artemis does that for FEFF fitting, and
> Athena will do a linear combination sum ("plot data + sum" with weights
> entered into the LCF standards boxes), but I don't see a way to get it to
> report the statistics.
>
> Here's the reason I'd like to be able to do this: when I run LCF fits, I
> often do one fit for XANES and another on chi(k) for EXAFS (and perhaps
> another using the derivative of XANES, just for good measure). The fits
> unsurprisingly usually give somewhat different weights to each fraction. So
> suppose XANES tells me my sample is 0.22 A and 0.78 B, and EXAFS tells me its
> 0.28 A and 0.72 B. I'd like to be able to force the EXAFS to 0.22 A and 0.78
> B (i.e. the results of the XANES fit), and have it give me an R-factor for
> that sum. Then I could apply something like a Hamilton test to decide if
> they're actually consistent.
>
> If it's not currently a feature, it's one I'd like to see. It's not that high
> a priority--I can just export the spectra and calculate it in Excel. But it
> would be nice.
It should be possible to calculate an R-factor or chi-square
statistics with a fairly simple ifeffit macro, using the functions
vsum() (to sum an array) and npts(). Something like (untested,
top-of-my-head):
macro show_rfact my.data my.model
_fit.d = $1 - $2
mean = vsum(_fit.d)/npts(_fit.d)
variance = vsum(_fit.d**2)/npts(_fit.d) - mean*mean
stderr = sqrt(variance)
rfact= vsum(_fit.d**2) / vsum($1**2)
print ' statistics for fit:'
print ' mean +/- standard_error = ', mean, ' +/-', stderr
print ' rfactor = ' rfact
end macro
Hope that helps
--Matt
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Re: [Ifeffit] Different R-factor values
Hi Jason, Chris, On Fri, Jan 25, 2013 at 10:01 AM, Jason Gaudet wrote: > Hi Chris, > > Might be helpful also to link to the archived thread you're talking about. > > http://millenia.cars.aps.anl.gov/pipermail/ifeffit/2006-June/007048.html > > Bruce might have to correct me on this, but if I remember right there were > individual-data-set R-factor and chi-square calculations at some point, > which come not from IFEFFIT but from Bruce's own post-fit calculations, and > these eventually were found to be pretty buggy and were dropped. > > I don't understand what "the average over the k weights" R factor is; > analyzing the same data set with multiple k weights (which is pretty > typical) still means a single fit result and a single statistical output in > IFEFFIT, as far back as I can remember, anyhow. The discussion about > multiple R-factors is for when you're simultaneously fitting multiple data > sets (i.e. trying to fit a couple different data sets to some shared or > partially shared set of guess variables). > > I think the overall residuals and chi-square are the more statistically > meaningful values, as they are actually calculated by the same algorithm > used to determine the guess variables - they're the quantities IFEFFIT is > attempting to reduce. I don't believe I've reported the per-data-set > residuals in my final results, as I only treated it as an internal check for > myself. (It would be nice to have again, though...) > > -Jason I can understand the desire for "per data set" R-factors. I think there are a few reasons why this hasn't been done so far. First, The main purpose of chi-square and R-factor are to be simple, well-defined statistics that can be used to compare different fits. In the case of R-factor, the actual value can also be readily interpreted and so mapped to "that's a good fit" and "that's a poor fit" more easily (even if still imperfect). Second, it would be a slight technical challenge for Ifeffit to make these different statistics and decide what to call them. Third, this is really asking for information on different portions of the fit, and it's not necessarily obvious how to break the whole into parts. OK, for fitting multiple data sets, it might *seem* obvious how to break the whole. But, well, fitting with multiple k-weights *is* fitting different data. Also, multiple-data-set fits can mix fits in different fit spaces, with different k-weights, and so on. Should the chi-squared and R-factors be broken up for different k-weights too? Perhaps they should. You can different weights to different data sets in a fit, but how to best do this can quickly become a field of study on its own. I guess that's not a valid reason to not report these So, again, I think it's reasonable to ask for per-data-set and/or per-k-weight statistics, but not necessarily obvious what to report here. For example, you might also want to use other partial sums-of-squares (based on k- or R-range, for example) to see where a fit was better and worse.Of course, you can calculate any of the partial sums and R-factors yourself. This isn't so obvious with Artemis or DArtemis, but it is possible. It's much easier to do yourself and implement for others with larch than doing it in Ifeffit or Artemis. Patches welcome for this and/or any other advanced statistical analyses. Better visualizations of the fit and/or mis-fit might be useful to think about too. --Matt ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
Re: [Ifeffit] error
Hi JeongEunSuk, 2011/1/11 JeongEunSuk : > Hi all > I fitted ZnMgO to know whether Mg is sited on Zn position. > the method of fitting as following; > 1st : to fit with some Mg located on Zn site. > 2nd: to fit with some Mg which position is different from Zn cite > The parameters for Mg like bonding length, disorder and others were set. > When I was fitting, there are only 8 parameters in both two method. So that > independent data point and variables are same. > > Both 1st and 2nd had same R-factor but reduced chi-square of 1st was lager > than that of 2nd. > It has been known that R-factor is independent of error( uncertainty in the > measurement) but reduced > chi-squrare is inverse proportional to error^2. > So I think that same R-factor and different reduced chi-square for two > method mean the fittings of two method are not different, > but error used in reduced chi-square is different. > I want to know how the error used in reduced chi-square is decided in FEFFIT > code. The details of the fit statistics have been explained in many places. Since your questions are about numerical values being "the same" and "different", it would be helpful to see some of the numerical values from a log file or project file. --Matt ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
Re: [Ifeffit] ifeffit R-factor
Hi Sandra, On Sat, Apr 6, 2013 at 12:37 PM, Sandra Luber wrote: > Dear Matt Newville, > > I do some fitting with ifeffit using EXAFS data generated by feff. > I wonder how the R-factor is calculated. Unfortunately, > I have not found any definition yet. Would it be possible > that you write me how it is obtained? > This would be great. > > Thanks a lot. > > Best regards > Sandra Luber > The basic definition is R = Sum( |data - fit|^2 ) / Sum( |data|^2 ) The old Feffit document probably has the clearest definition, in its Chapter 5 (pages 16-20 of http://cars.uchicago.edu/~newville/feffit/feffit.pdf ). The definition and briefer explanations are also given in several of the tutorials on http://xafs.org/Tutorials. Thanks for reminding me to put this and related information into the Larch documentation! --Matt ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
Re: [Ifeffit] Ifeffit Digest, Vol 119, Issue 19
Hello Chris. - I don't have an answer regarding the R-factor. - Noise or glitch: how does I0 look like? Is the glitch you suspect visible in I0 at this energy? If you're refering to the feature that points downwards at 8A-1, it actually shifts with the spectra (I can see two groups of spectra in this k-range) so a glitch seems doubtful to me. Can you tell more about the collection of data (transmission, fluorescence, thickness of the sample, temperature, etc.)? By looking at the data, and if you confirm that I0 is glitch-free, I would be more suspicious about the data in the range 10-14A-1 than this 8A-1 feature. Cheers denis Today's Topics: 1. k-range question & R-factor (Christopher Patridge) Hello Users, I was looking for an opinion about the chi(k) signal in a set of data I am analyzing. Brief background, this is a set of in-situ XAS data collected at the Fe K edge from a working electrochemical cell at a range of potentials during charge; I did not collect the data. I suspect the feature at ~ 8 angstroms-1, although present in all the spectra is noise or glitch and wondered if I am being overly cautious? My conservative range ( k = 2-7 and R = 1-2) really constrains the model Nidp = 3.31. Luckily, multiple datasets ( 8 ) to the rescue to give me some flexibility. In a multiple dataset fitting, is the R-factor of the whole set just the average or total mismatch across all the datasets or it calculated another way? Working towards happiness, Chris Patridge -- Denis Testemale Institut Néel FAME beamline at ESRF +33 476 881 045 ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
[Ifeffit] Chi in arthemis
Hi Scott, here I copy a part of the report: Independent points = 6.222656250 Number of variables = 4.0 Chi-square = 247.145092496 Reduced Chi-square = 111.193574128 R-factor= 0.017422216 Guess parameters +/- uncertainties (initial guess): amp = 6.7815290 +/- 1.4687660(1.) enot= 2.2173620 +/- 2.1499920(0.) delr= 0.0514640 +/- 0.0163900(0.) ss = 0.0074020 +/- 0.0025220(0.0030) I see that the R-factor is pretty good, 1.74%, amp is high cause is correlated with the coordination number and always have big errors., delr has the error of the total distance, so it is ok, but ss and enot have a a really big error, is this normal? Thanks, euG ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
[Ifeffit] Find R-factor for linear combination sums?
Hi all,
Is there a way to get Athena (or Ifeffit) to report an R-factor for a linear
combination sum, as opposed to a fit? Artemis does that for FEFF fitting, and
Athena will do a linear combination sum ("plot data + sum" with weights entered
into the LCF standards boxes), but I don't see a way to get it to report the
statistics.
Here's the reason I'd like to be able to do this: when I run LCF fits, I often
do one fit for XANES and another on chi(k) for EXAFS (and perhaps another using
the derivative of XANES, just for good measure). The fits unsurprisingly
usually give somewhat different weights to each fraction. So suppose XANES
tells me my sample is 0.22 A and 0.78 B, and EXAFS tells me its 0.28 A and 0.72
B. I'd like to be able to force the EXAFS to 0.22 A and 0.78 B (i.e. the
results of the XANES fit), and have it give me an R-factor for that sum. Then I
could apply something like a Hamilton test to decide if they're actually
consistent.
If it's not currently a feature, it's one I'd like to see. It's not that high a
priority--I can just export the spectra and calculate it in Excel. But it would
be nice.
--Scott Calvin
Sarah Lawrence College
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Re: [Ifeffit] running ifeffit under 64-bit windows7
Hi, maybe these below clarify a little bit the problem, but the problem sounds very intriguing http://millenia.cars.aps.anl.gov/pipermail/ifeffit/2004-July/005729.html http://millenia.cars.aps.anl.gov/pipermail/ifeffit/2005-October/006613.html http://cars9.uchicago.edu/ifeffit/FAQ/FeffitModeling I am waiting also for the answer from authors Do you see changes in the fit in R or/and K space, between systems? I suppose that all input parameters were identical... regards kicaj W dniu 12-03-10 15:17, Sameh Ibrahim Ahmed pisze: Hi, I have used ARTEMIS to fit the EXAFS of a simple Cu foil with the two diffrent machines, a 32 bit and 64 bit ones, both running widows7, 32 ans 64 bit respectively. The results obtained are slightly different, I have appended the message with these results. the very low value of R-factor produced with the 64bit system is difficult to interpret. the questions are; 1- how to account for these differences? 2- if I to publish something, which measure of the quality should I present? and how can I interpret it? regards Sameh 32bit windows 7 Independent points = 12.172851562 Number of variables = 6.0 Chi-square = 53.001967099 Reduced Chi-square = 8.586301900 R-factor= 0.000163791 !!! Measurement uncertainty (k) = 0.000110566 Measurement uncertainty (R) = 0.057163282 Number of data sets = 1.0 Guess parameters +/- uncertainties (initial guess): amp = 0.9907500 +/- 0.0312520(1.) enot= 5.6814210 +/- 0.3815760(0.) delr1 = 0.0016460 +/- 0.0033990(0.) ss1 = 0.0099820 +/- 0.0004090(0.0030) w1 3rd cumulant = 0.0001710 +/- 0.340(0.) p1 4th cumulant = 0.240 +/- 0.070(0.) 64bit windows 7 Independent points = 12.172851562 Number of variables = 6.0 Chi-square = 54.036163164 Reduced Chi-square = 8.753841335 R-factor= 0.309664502E-06 !!! Measurement uncertainty (k) = 0.97377 Measurement uncertainty (R) = 0.050344538 Number of data sets = 1.0 Guess parameters +/- uncertainties (initial guess): amp = 1.0029100 +/- 0.0296670(1.) enot= 5.7522760 +/- 0.4614510(0.) delr1 = 0.0024980 +/- 0.0040190(0.) ss1 = 0.0101430 +/- 0.0003790(0.0030) w1 3rd cumulant = 0.0001780 +/- 0.410(0.) p1 4th cumulant = 0.260 +/- 0.070(0.) ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
[Ifeffit] N independent variables
Dear list, I made an EXAFS analysis in Artemis (in Demeter 0.9.22) using all the available variables. This is a fragment of the .log file I got: Independent points : 17.7666016 Number of variables : 17 Chi-square : 265.0947132 Reduced chi-square : 345.8050781 R-factor: 0.0026486 Number of data sets : 1 : k-range = 2.942 - 11.043 : dk= 1 : k-window = hanning : k-weight = 1,2,3 : R-range = 1.115 - 3.5 : dR= 0.0 : R-window = hanning : fitting space = r : background function = yes : phase correction = no : background removal= E0: 20002.215, Rbkg: 1.0, range: [2.25:17.4039986832903], clamps: 0/24, kw: 2 : epsilon_k by k-weight = 3.189e-004 : epsilon_r by k-weight = 2.339e-001 : R-factor by k-weight = 1 -> 0.00220, 2 -> 0.00224, 3 -> 0.00392 The problem is that when I use the Nyquist criterion Nind=2*deltak*deltar/pi + 1 for calculating the number of independent points the value I got is much lower and close to 13. I was not aware of this discrepancy and it caused a reviewer to think I made up the fit! Am I doing something wrong? Is there another way to calculate the Nind that might have been used by Artemis? I would really appreciate any help. Yours Jesús ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit Unsubscribe: http://millenia.cars.aps.anl.gov/mailman/options/ifeffit
Re: [Ifeffit] Chi in arthemis
Matt, Is this the most recent IXAS report on error reporting standards? http://www.i-x-s.org/OLD/subcommittee_reports/sc/err-rep.pdf It uses a rather expansive definition of epsilon, which explicitly includes "imperfect" ab initio standards such as FEFF calculations. It indicates that statistical methods such as that used by ifeffit for estimating measurement error yields a lower limit for epsilon, and thus an overestimate of chi square. So I think my statement and yours are entirely compatible. As far as what should be reported, I do deviate from the IXAS recommendations by not reporting chi-square. Of course, I tend to work in circumstances where the signal-to-noise ratio is very high, and thus the statistical uncertainties make a very small contribution to the overall measurement error. In such cases I have become convinced that the R-factor alone provides as much meaningful information as the chi-square values, and that in fact the chi-square values can be confusing when listed for fits on different data. For those working with dilute samples, on the other hand, I can see that chi-square might be a meaningful quantity. At any rate, I strongly agree that the decision of which measurements of quality of fit to produce should not be dependent on what "looks good"! That would be bad science. The decision of what figures of merit to present should be made a priori. --Scott Calvin Sarah Lawrence College On Aug 18, 2009, at 10:40 PM, Matt Newville wrote: > Having a "reasonable R-factor" of a few percent misfit and a reduced > chi-square of ~100 means the misfit is much larger than the estimated > uncertainty in the data. This is not at all unusual. It does not > necessarily mean (as Scott implies) that this is because the > uncertainty in data is unreasonably low, but can also mean that there > are systematic problems with the FEFF calculations that do not account > for the data as accurately as it can be measured. For most "real" > data, it is likely that both errors FEFF and a slightly low estimate > for the uncertainty in the data contribute to making reduced > chi-square much larger than 1. > > And, yes, the community-endorsed recommendation is to report either > chi-square or reduced chi-square as well as an R-factor. I think some > referees might find it a little deceptive to report R-factor because > it is "acceptably small" but not reduced chi-square because it is "too > big". ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
Re: [Ifeffit] running ifeffit under 64-bit windows7
Hi Kicaj, 2012/3/10 "Dr. Dariusz A. Zając" : > Hi, > maybe these below clarify a little bit the problem, but the problem sounds > very intriguing > http://millenia.cars.aps.anl.gov/pipermail/ifeffit/2004-July/005729.html > http://millenia.cars.aps.anl.gov/pipermail/ifeffit/2005-October/006613.html > http://cars9.uchicago.edu/ifeffit/FAQ/FeffitModeling > > I am waiting also for the answer from authors I would have said these questions have been answered, but maybe I misunderstand... What is the question you are waiting to be answered? All of chi-square, reduced chi-square, and R factor express the sum of squares of the residual (data-model) after a fit has finished. The difference between these statistics is how they are scaled. In particular, chi-square is scaled by the estimated error in the data. If you look at a (naive?) introduction to statistics, you will see it stated that this should be approximately the number of degrees of freedom in the fit. Reduced chi-square is then defined to be chi-squared / (the number of degrees of freedom in the fit), so that it should be 1 (according to statistics 101). This presupposes a couple of things that aren't very true for us: a) it assumes we actually know the uncertainty in the data -- the automated estimate in ifefit is pretty simplistic. b) it assumes our model of the data is much better than that data uncertainty. Many people describe these as "systematic errors" and include alll sorts of data processing artifacts as well as errors in the Feff calculations. For us, reduced chi-square is almost always >> 1, unless the data is very noisy. R-factor scales the fit residual by the magnitude of the data itself, for some estimate of "fractional misfit". This gives a convenient measure that is independent of the scale of the data (and so also independent of data k-range and k-weight for fits in R-space), and can more easily be made into a "rule of thumb", say "If R-factor > 0.05, then you should be wary of the results". Hope that helps, --Matt ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
Re: [Ifeffit] Find R-factor for linear combination sums?
On Saturday, January 07, 2012, 01:42:43 pm, Scott Calvin wrote:
> Hi all,
>
> Is there a way to get Athena (or Ifeffit) to report an R-factor for a
> linear combination sum, as opposed to a fit? Artemis does that for FEFF
> fitting, and Athena will do a linear combination sum ("plot data + sum"
> with weights entered into the LCF standards boxes), but I don't see a way
> to get it to report the statistics.
>
> Here's the reason I'd like to be able to do this: when I run LCF fits, I
> often do one fit for XANES and another on chi(k) for EXAFS (and perhaps
> another using the derivative of XANES, just for good measure). The fits
> unsurprisingly usually give somewhat different weights to each fraction.
> So suppose XANES tells me my sample is 0.22 A and 0.78 B, and EXAFS tells
> me its 0.28 A and 0.72 B. I'd like to be able to force the EXAFS to 0.22 A
> and 0.78 B (i.e. the results of the XANES fit), and have it give me an
> R-factor for that sum. Then I could apply something like a Hamilton test
> to decide if they're actually consistent.
>
> If it's not currently a feature, it's one I'd like to see. It's not that
> high a priority--I can just export the spectra and calculate it in Excel.
> But it would be nice.
That's a reasonable request. I'll put it on the to do list for the new
version of Athena.
B
--
Bruce Ravel bra...@bnl.gov
National Institute of Standards and Technology
Synchrotron Methods Group at NSLS --- Beamlines U7A, X24A, X23A2
Building 535A
Upton NY, 11973
My homepage:http://xafs.org/BruceRavel
EXAFS software: http://cars9.uchicago.edu/~ravel/software/exafs/
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Re: [Ifeffit] Query regarding error bars
Hi Bindu, There are lots of descriptions of these concepts on the exafs.org web page. Check out the Tutorials page. I wrote about them in my book chapter on page 58. If you like, I can send you a copy. It is kinda big so you will need to have 8Meg space in your mail box. Shelly -Original Message- From: ifeffit-boun...@millenia.cars.aps.anl.gov on behalf of Bindu R. Sent: Fri 1/9/2009 7:12 AM To: ifeffit@millenia.cars.aps.anl.gov Subject: [Ifeffit] Query regarding error bars Hi all, Could any tell me in a simple language about the error bars returned by the EXAFS fitting program? what do they exactly represent?How is it determined?How is the number of iterations decided.In addition to R-factor what are the other parameters which determines a good fit.For a R-factor ~0.001, if the value of chi2~10,000 and reduced chi2 ~ 500, can one consider the fit to be good even if one gets a good match to the experimental spectra. Bindu Dr.Bindu R. Visiting Fellow BG-37 DCMP&MS Tata Institute of Fundamental Research Homi Bhabha Road Colaba Mumbai-400 005 India Contact Number Lab- 022-2278 2256, 022-2278 2671 Mobile-919892536830 Add more friends to your messenger and enjoy! Go to http://messenger.yahoo.com/invite/ <>___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
Re: [Ifeffit] Per-data set R-factor
Lyle, Thanks for your email. It is easy to let items on the to do list languish if no one makes any noise. Knowing that you are interested is helpful. To be honest, I cannot remember why I disabled that feature. I'll look into it. Perhaps I'll be able to get it into the next release. In the immediate, you certainly can compute it. You can save the data and fit to a column data file and do whatever statistical assessment you want. The question about automated export of the data is an interesting one. Currently, Artemis does not offer to do things like write column data file output at the end of a fit, but that is reasonable and maybe even useful. I'll think about that as well. Cheers, B On Thursday, December 20, 2012 11:19:57 PM Lyle Gordon wrote: > Dear iffefit users, > > I am using the latest version of Demeter/Artemis to fit some EXAFS > data. I'm running Win 7 64. > > I found in Horae that when I fit multiple datasets it would output the > R-factor for each dataset in the fit. I would really like these values > in the newest version. > > I found on the todo list > (https://github.com/bruceravel/demeter/blob/master/todo.org) > > [ ] per-data set R-factor reporting in log file is turned off. > > Is there a simple way to turn this "on"? > > If not I guess I can calculate it by hand from the Re/Im terms of the > R space data and fit. To that end, if I have a few datasets it is > tedious to export the data/fit files for each sample. Is there an > automated way to export this data? > > Thanks very much, > Lyle > > -- > Lyle Gordon > Department of Materials Science and Engineering > Northwestern University > > 2220 Campus Drive > Cook Hall 2036 > Evanston, IL 60208 > > Tel: (847) 491-3584 > Mobile: (847) 400-4071 > http://lylegordon.ca > ___ > Ifeffit mailing list > Ifeffit@millenia.cars.aps.anl.gov > http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit -- Bruce Ravel bra...@bnl.gov National Institute of Standards and Technology Synchrotron Methods Group at NSLS --- Beamlines U7A, X24A, X23A2 Building 535A Upton NY, 11973 Homepage:http://xafs.org/BruceRavel Software:https://github.com/bruceravel ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
[Ifeffit] path contribution to fit in low R-space position, but the fit bond length is much longer than that
Dear all, I fit a Zn cluster which RDF has a peak little lower than Zn-S peak,and has a shoulder near Zn-O.This accords with my expection the cluster may have both Zn-S Zn-O bond.But after fit the Zn-O bond length is much larger than reff while it path contribution after fit did in low R.What's wrong with my fit?is it the big delro & delrs =0.7882? sincerely, zhanfei this is the fit log,and puc of fit and path contribution is attached Independent points : 8.0087891 Number of variables : 5 Chi-square : 2276.2312227 Reduced chi-square : 756.5273522 R-factor: 0.0023036 Measurement uncertainty (k) : 0.0002947 Measurement uncertainty (R) : 0.0004735 Number of data sets : 1 Happiness = 100.00/100 color = #D8E796 * Note: happiness is a semantic parameter and should * *NEVER be reported in a publication -- NEVER!* guess parameters: enot = 8.99859575# +/- 1.30831421 [0] ssS= 0.01038392# +/- 0.00062570 [0.00300] delrS = 0.01271583# +/- 0.00971686 [0] ssO= 0.02806760# +/- 0.00277795 [0.00300] delrO = 0.33252269# +/- 0.01446304 [0] set parameters: amp= 0.8500 OC = 0.01068708 Correlations between variables: delrs & enot --> 0.9345 delro & enot --> 0.8636 delro & delrs --> 0.7882 sso & enot --> -0.7422 delro & sso--> -0.6014 sso & delrs --> -0.5887 sss & enot --> 0.4980 delrs & sss--> 0.4803 sso & sss--> -0.4737 All other correlations below 0.4 = Data set >> CdSe-ZnS(Fe)-Zn << : Athena project = C:\04-6-29wulizhu\Zn\athena.prj, 3 : name = CdSe-ZnS(Fe)-Zn : k-range = 3.000 - 10 : dk = 1 : k-window = hanning : k-weight = 1,2,3 : R-range = 1.15 - 3 : dR = 0.0 : R-window = hanning : fitting space= r : background function = no : phase correction = : R-factor by k-weight = 1 -> 0.01310, 2 -> 0.01474, 3 -> 0.02004 nameN S02 sigma^2 e0 delr Reff R = O1.1 6.360 0.850 0.02807 8.999 0.33252 1.97800 2.31052 S7.1 3.600 0.850 0.01038 8.999 0.01272 2.34200 2.35472 nameei third fourth = O1.1 0.0 0.01069 0.0 S7.1 0.0 0.0 0.0 ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
Re: [Ifeffit] k-range question & R-factor
Thank you Scott, I guess that is a refinement of my question concerning R-factor.' Chris Christopher J. Patridge, PhD NRC Post Doctoral Research Associate Naval Research Laboratory Washington, DC 20375 Cell: 315-529-0501 On 1/15/2013 9:39 AM, Scott Calvin wrote: Hi Chris, I don't see a reason to think that data is a glitch. For one thing, it's not consistent across datasets. The features also look smooth, and not so glitch-like. The spike around 8.2 inverse angstroms in some of the datasets looks a bit more like a glitch, but it's fairly modest and narrow enough not to mess you up too much. The spacing of those features look OK--there's a double feature in some of the datasets around 6-7 inverse angstroms; it's plausible there would be another reature like that above it. In fact, I can make an argument that there's some kind of beating going on that gives a shoulder at 3.5-5, a double peak at 5-7, and two peaks at 7-8 inverse angstroms. So I would recommend including that data and seeing what it does to your fits. If that range is garbage, your fits will probably reject it. As for your second question, R-factors are always a kind of average across the data, by definition. So "total" mismatch doesn't really make sense. Off-hand, though, I don't recall how ifeffit weights the data for the purposes of calculating R-factors for multiple datasets, and that may be your question. --Scott Calvin Sarah Lawrence College On Jan 15, 2013, at 9:21 AM, Christopher Patridge wrote: Hello Users, I was looking for an opinion about the chi(k) signal in a set of data I am analyzing. Brief background, this is a set of in-situ XAS data collected at the Fe K edge from a working electrochemical cell at a range of potentials during charge; I did not collect the data. I suspect the feature at ~ 8 angstroms-1, although present in all the spectra is noise or glitch and wondered if I am being overly cautious? My conservative range ( k = 2-7 and R = 1-2) really constrains the model Nidp = 3.31. Luckily, multiple datasets ( 8 ) to the rescue to give me some flexibility. In a multiple dataset fitting, is the R-factor of the whole set just the average or total mismatch across all the datasets or it calculated another way? Working towards happiness, Chris Patridge -- Christopher J. Patridge, PhD NRC Post Doctoral Research Associate Naval Research Laboratory Washington, DC 20375 Cell: 315-529-0501 ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
Re: [Ifeffit] N independent variables
Jesus, On Mon, May 23, 2016 at 2:07 PM, Jesús Eduardo Vega Castillo < jeve...@gmail.com> wrote: > Dear list, > > I made an EXAFS analysis in Artemis (in Demeter 0.9.22) using all the > available variables. This is a fragment of the .log file I got: > > Independent points : 17.7666016 > Number of variables : 17 > Chi-square : 265.0947132 > Reduced chi-square : 345.8050781 > > R-factor: 0.0026486 > > Number of data sets : 1 > : k-range = 2.942 - 11.043 > : dk= 1 > : k-window = hanning > : k-weight = 1,2,3 > : R-range = 1.115 - 3.5 > : dR= 0.0 > : R-window = hanning > : fitting space = r > : background function = yes > : phase correction = no > : background removal= E0: 20002.215, Rbkg: 1.0, range: > [2.25:17.4039986832903], clamps: 0/24, kw: 2 > : epsilon_k by k-weight = 3.189e-004 > : epsilon_r by k-weight = 2.339e-001 > : R-factor by k-weight = 1 -> 0.00220, 2 -> 0.00224, 3 -> 0.00392 > > The problem is that when I use the Nyquist criterion > > Nind=2*deltak*deltar/pi + 1 > > for calculating the number of independent points the value I got is much > lower and close to 13. > > I was not aware of this discrepancy and it caused a reviewer to think I > made up the fit! > > Sending the entire log file is always recommended. Otherwise, you are selectively editing what you are telling us, and expecting us to guess what you haven't told us. Sending the project file is often a good choice. Fortunately, you included an important clue. You have "background function = yes", which means the fit will actually extend down to R=0, using your Rmin as Rbkg in calculating how many variables are used for the spline. With that included, the fit does contain approximately 18 independent parameters, about 5 of which will be used for the background subtraction. --Matt ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit Unsubscribe: http://millenia.cars.aps.anl.gov/mailman/options/ifeffit
Re: [Ifeffit] running ifeffit under 64-bit windows7
Dear Matt, when I was answering I didnt received your answer... waiting for the answer from authors means that I suspect perhaps a problem with distribution version, what you already suggested... sorry for the confussion by my email... cheers darek/kicaj W dniu 12-03-10 17:16, Matt Newville pisze: Hi Kicaj, 2012/3/10 "Dr. Dariusz A. Zając": Hi, maybe these below clarify a little bit the problem, but the problem sounds very intriguing http://millenia.cars.aps.anl.gov/pipermail/ifeffit/2004-July/005729.html http://millenia.cars.aps.anl.gov/pipermail/ifeffit/2005-October/006613.html http://cars9.uchicago.edu/ifeffit/FAQ/FeffitModeling I am waiting also for the answer from authors I would have said these questions have been answered, but maybe I misunderstand... What is the question you are waiting to be answered? All of chi-square, reduced chi-square, and R factor express the sum of squares of the residual (data-model) after a fit has finished. The difference between these statistics is how they are scaled. In particular, chi-square is scaled by the estimated error in the data. If you look at a (naive?) introduction to statistics, you will see it stated that this should be approximately the number of degrees of freedom in the fit. Reduced chi-square is then defined to be chi-squared / (the number of degrees of freedom in the fit), so that it should be 1 (according to statistics 101). This presupposes a couple of things that aren't very true for us: a) it assumes we actually know the uncertainty in the data -- the automated estimate in ifefit is pretty simplistic. b) it assumes our model of the data is much better than that data uncertainty. Many people describe these as "systematic errors" and include alll sorts of data processing artifacts as well as errors in the Feff calculations. For us, reduced chi-square is almost always>> 1, unless the data is very noisy. R-factor scales the fit residual by the magnitude of the data itself, for some estimate of "fractional misfit". This gives a convenient measure that is independent of the scale of the data (and so also independent of data k-range and k-weight for fits in R-space), and can more easily be made into a "rule of thumb", say "If R-factor> 0.05, then you should be wary of the results". Hope that helps, --Matt ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
Re: [Ifeffit] running ifeffit under 64-bit windows7
Hi Kicaj, OK, sorry I misunderstood then. And, despite my laziness, I think that Sameh is right that it's probably time for a more complete update Such a thing should probably feature Bruce's newer codes of course. --Matt On Sat, Mar 10, 2012 at 10:16 AM, Matt Newville wrote: > Hi Kicaj, > > 2012/3/10 "Dr. Dariusz A. Zając" : >> Hi, >> maybe these below clarify a little bit the problem, but the problem sounds >> very intriguing >> http://millenia.cars.aps.anl.gov/pipermail/ifeffit/2004-July/005729.html >> http://millenia.cars.aps.anl.gov/pipermail/ifeffit/2005-October/006613.html >> http://cars9.uchicago.edu/ifeffit/FAQ/FeffitModeling >> >> I am waiting also for the answer from authors > > I would have said these questions have been answered, but maybe I > misunderstand... What is the question you are waiting to be answered? > > All of chi-square, reduced chi-square, and R factor express the sum of > squares of the residual (data-model) after a fit has finished. The > difference between these statistics is how they are scaled. > > In particular, chi-square is scaled by the estimated error in the > data. If you look at a (naive?) introduction to statistics, you will > see it stated that this should be approximately the number of degrees > of freedom in the fit. Reduced chi-square is then defined to be > chi-squared / (the number of degrees of freedom in the fit), so that > it should be 1 (according to statistics 101). This presupposes a > couple of things that aren't very true for us: > a) it assumes we actually know the uncertainty in the data -- the > automated estimate in ifefit is pretty simplistic. > b) it assumes our model of the data is much better than that data > uncertainty. Many people describe these as "systematic errors" and > include alll sorts of data processing artifacts as well as errors in > the Feff calculations. > > For us, reduced chi-square is almost always >> 1, unless the data is very > noisy. > > R-factor scales the fit residual by the magnitude of the data itself, > for some estimate of "fractional misfit". This gives a convenient > measure that is independent of the scale of the data (and so also > independent of data k-range and k-weight for fits in R-space), and can > more easily be made into a "rule of thumb", say "If R-factor > 0.05, > then you should be wary of the results". > > Hope that helps, > > --Matt -- --Matt Newville 630-252-0431 ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
Re: [Ifeffit] Running (D)Artemis yields different result from that shown in (D)Artemis instruction videos
Ku-Ding, I don't know what to tell you. On the computer I am sitting in front of right now, I opened your two project files and hit the fit buttons, I get the same fit with only numerical differences. Here I am cutting and pasting from the two log files: old artemis: Chi-square =4334.684537717 Reduced Chi-square = 691.819976095 R-factor= 0.004250325 amp = 0.8649100 +/- 0.0412220(1.) enot= 5.6049380 +/- 0.2950270(0.) delr=-0.0226780 +/- 0.0023790(0.) ss = 0.0082230 +/- 0.0003250(0.0030) new artemis: Chi-square : 4348.7359268 Reduced chi-square : 694.0625918 R-factor: 0.0042652 amp= 0.86526150# +/- 0.04129645 [1.0] enot = 5.61081742# +/- 0.29527844 [0] delr = -0.02266589# +/- 0.00238341 [0] ss = 0.00822546# +/- 0.00032571 [0.00300] I don't acknowledge that there is a problem. B From: ifeffit-boun...@millenia.cars.aps.anl.gov [ifeffit-boun...@millenia.cars.aps.anl.gov] on behalf of Tsuei, Ku-Ding [ts...@nsrrc.org.tw] Sent: Thursday, October 18, 2012 1:15 PM To: ifeffit@millenia.cars.aps.anl.gov Subject: [Ifeffit] Running (D)Artemis yields different result from that shown in (D)Artemis instruction videos Hi Bruce, I went through your (D)Artemis instruction videos and ran the latest Demetris 0.9.12 with 0.9.13 update side by side to reproduce the results. However, my running yields much poorer fitting results on Au foil EXAFS, even the first shell (video 03). Actually it happened using the older 0.9.11 too. I also went through your Lecture videos shot at Diamond and ran (D)Artemis but could reproduce your results closely. I have felt puzzled for quite a while why the simplest case Au foil does work well. Today I tried to run the same Au data and fitting by the old, last version of Artemis 0.8.014. I could produce very good fitting on the first shell with the R-factor very near that shown in the video. I made sure the math expressions for the fitting parameters amp, enot, delr and ss are set exactly the same, with fitting range exactly the same, in both programs. Their screen outputs file is attached. The saved respective project files are also attached. I copied the fit outputs into their journals. I would appreciate if you may review these results and help clear my puzzle. Best regards, Ku-Ding ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
Re: [Ifeffit] Chi in arthemis
OK, I feel I have to weigh in. I'm on a microprobe line where sample motions contribute to noise and I rarely find that the noise quality of the EXAFS signal, as measured by running a high-order polynomial through the data and looking at the residuals, matches the number of counts per point. Also, if you are using an analog counter like an ion chamber, then you can't measure the true number of detected quanta, so you can't get the shot-noise limit. Further, there will be systematics like background-subtraction artifacts which will act as other than white noise. For all these reasons, I think that an attempt to use a literal chi-squared isn't going to succeed. I don't think I've ever seen anyone report the true noise quality of their data, anyway. Occasionally, someone might report the number of counts/point, but as I said, that's an upper limit to the noise quality. What is more intuitive, though less rigorous to report, is the R value. mam - Original Message - From: "Scott Calvin" To: "XAFS Analysis using Ifeffit" Sent: Tuesday, August 18, 2009 8:30 PM Subject: Re: [Ifeffit] Chi in arthemis > Matt, > > Is this the most recent IXAS report on error reporting standards? > > http://www.i-x-s.org/OLD/subcommittee_reports/sc/err-rep.pdf > > It uses a rather expansive definition of epsilon, which explicitly > includes "imperfect" ab initio standards such as FEFF calculations. It > indicates that statistical methods such as that used by ifeffit for > estimating measurement error yields a lower limit for epsilon, and > thus an overestimate of chi square. > > So I think my statement and yours are entirely compatible. > > As far as what should be reported, I do deviate from the IXAS > recommendations by not reporting chi-square. Of course, I tend to work > in circumstances where the signal-to-noise ratio is very high, and > thus the statistical uncertainties make a very small contribution to > the overall measurement error. In such cases I have become convinced > that the R-factor alone provides as much meaningful information as the > chi-square values, and that in fact the chi-square values can be > confusing when listed for fits on different data. For those working > with dilute samples, on the other hand, I can see that chi-square > might be a meaningful quantity. > > At any rate, I strongly agree that the decision of which measurements > of quality of fit to produce should not be dependent on what "looks > good"! That would be bad science. The decision of what figures of > merit to present should be made a priori. > > --Scott Calvin > Sarah Lawrence College > > On Aug 18, 2009, at 10:40 PM, Matt Newville wrote: > >> Having a "reasonable R-factor" of a few percent misfit and a reduced >> chi-square of ~100 means the misfit is much larger than the estimated >> uncertainty in the data. This is not at all unusual. It does not >> necessarily mean (as Scott implies) that this is because the >> uncertainty in data is unreasonably low, but can also mean that there >> are systematic problems with the FEFF calculations that do not account >> for the data as accurately as it can be measured. For most "real" >> data, it is likely that both errors FEFF and a slightly low estimate >> for the uncertainty in the data contribute to making reduced >> chi-square much larger than 1. >> >> And, yes, the community-endorsed recommendation is to report either >> chi-square or reduced chi-square as well as an R-factor. I think some >> referees might find it a little deceptive to report R-factor because >> it is "acceptably small" but not reduced chi-square because it is "too >> big". > > ___ > Ifeffit mailing list > Ifeffit@millenia.cars.aps.anl.gov > http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit > ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
Re: [Ifeffit] Running (D)Artemis yields different result from that shown in (D)Artemis instruction videos
Bruce, Perhaps you noticed the "Fit color" was red (large R-factor 0.074496, poor fit, also seen in the attached figure in the last email) when you loaded in the project file I sent you. When you hit Fit button again the "Fit color" might turn to green indicating good fit as shown in your result of a much smaller R-factor (0.004265). I did the following test on various versions of Demeter on my desktop and notebook computers both installed with Windows 7 SP1. Of course I uninstalled one version first before installing another. I tried to use Uninstall within the Program menu or use the Program manager. I tried to reboot or not to reboot after uninstallation or installation. Neither shows any difference. Fit color 0.9.10 green 0.9.11 red 0.9.12 red 0.9.13 red Only version 0.9.10 yields good fit. The latter versions would not give good fits even with repeated hitting the "Fit" button. I have no idea what causes these results but perhaps this observation provides a clue. Ku-Ding On 2012/10/22 上午 01:00, ifeffit-requ...@millenia.cars.aps.anl.gov wrote: Send Ifeffit mailing list submissions to ifeffit@millenia.cars.aps.anl.gov To subscribe or unsubscribe via the World Wide Web, visit http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit or, via email, send a message with subject or body 'help' to ifeffit-requ...@millenia.cars.aps.anl.gov You can reach the person managing the list at ifeffit-ow...@millenia.cars.aps.anl.gov When replying, please edit your Subject line so it is more specific than "Re: Contents of Ifeffit digest..." Today's Topics: 1. Re: Running (D)Artemis yields different result from that shown in (D)Artemis instruction videos (Ravel, Bruce) -- Message: 1 Date: Sun, 21 Oct 2012 12:36:10 + From: "Ravel, Bruce" To: XAFS Analysis using Ifeffit Subject: Re: [Ifeffit] Running (D)Artemis yields different result from that shown in (D)Artemis instruction videos Message-ID: <47ced3cd722c2a439c0d1d1056b2132517c3b...@ex10-mb1.bnl.gov> Content-Type: text/plain; charset="us-ascii" Ku-Ding, I don't know what to tell you. On the computer I am sitting in front of right now, I opened your two project files and hit the fit buttons, I get the same fit with only numerical differences. Here I am cutting and pasting from the two log files: old artemis: Chi-square =4334.684537717 Reduced Chi-square = 691.819976095 R-factor= 0.004250325 amp = 0.8649100 +/- 0.0412220(1.) enot= 5.6049380 +/- 0.2950270(0.) delr=-0.0226780 +/- 0.0023790(0.) ss = 0.0082230 +/- 0.0003250(0.0030) new artemis: Chi-square : 4348.7359268 Reduced chi-square : 694.0625918 R-factor: 0.0042652 amp= 0.86526150# +/- 0.04129645 [1.0] enot = 5.61081742# +/- 0.29527844 [0] delr = -0.02266589# +/- 0.00238341 [0] ss = 0.00822546# +/- 0.00032571 [0.00300] I don't acknowledge that there is a problem. B From:ifeffit-boun...@millenia.cars.aps.anl.gov [ifeffit-boun...@millenia.cars.aps.anl.gov] on behalf of Tsuei, Ku-Ding [ts...@nsrrc.org.tw] Sent: Thursday, October 18, 2012 1:15 PM To:ifeffit@millenia.cars.aps.anl.gov Subject: [Ifeffit] Running (D)Artemis yields different result from that shown in (D)Artemis instruction videos Hi Bruce, I went through your (D)Artemis instruction videos and ran the latest Demetris 0.9.12 with 0.9.13 update side by side to reproduce the results. However, my running yields much poorer fitting results on Au foil EXAFS, even the first shell (video 03). Actually it happened using the older 0.9.11 too. I also went through your Lecture videos shot at Diamond and ran (D)Artemis but could reproduce your results closely. I have felt puzzled for quite a while why the simplest case Au foil does work well. Today I tried to run the same Au data and fitting by the old, last version of Artemis 0.8.014. I could produce very good fitting on the first shell with the R-factor very near that shown in the video. I made sure the math expressions for the fitting parameters amp, enot, delr and ss are set exactly the same, with fitting range exactly the same, in both programs. Their screen outputs file is attached. The saved respective project files are also attached. I copied the fit outputs into their journals. I would appreciate if you may review these results and help clear my puzzle. Best regards, Ku-Ding --
Re: [Ifeffit] Artemis
OK, good answer Scott. My fits have lower values of R-factor but when I depict them in k-space they do not fit quite well to the experimental data due to the short range of R space chosen, of course if I increase range of R then I hope fits in k space will look better. When I talked about distant paths I mean paths contributing to other shells. I will consider MS but with simple constraints. Thank you very much Best regards, JA ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
Re: [Ifeffit] Chi in arthemis
Hi euG, That amp is not physically reasonable, unless you're using it as a proxy for the coordination number. The uncertainty on the other variables does not seem high to me for a single-shell fit. Well, 2 eV is a bit high for an uncertainty on E0, but not crazy high. There are some approaches that can be used to try to reduce the uncertainties, but you shouldn't even think about that until you get the amp (S02) straightened out. --Scott Calvin Sarah Lawrence College On Aug 18, 2009, at 6:18 PM, Eugenio Otal wrote: > Hi Scott, > here I copy a part of the report: > > Independent points = 6.222656250 > Number of variables = 4.0 > Chi-square = 247.145092496 > Reduced Chi-square = 111.193574128 > R-factor= 0.017422216 > > Guess parameters +/- uncertainties (initial guess): > amp = 6.7815290 +/- 1.4687660(1.) > enot= 2.2173620 +/- 2.1499920(0.) > delr= 0.0514640 +/- 0.0163900(0.) > ss = 0.0074020 +/- 0.0025220(0.0030) > > I see that the R-factor is pretty good, 1.74%, amp is high cause is > correlated with the coordination number and always have big errors., > delr has the error of the total distance, so it is ok, but ss and > enot have a a really big error, is this normal? > Thanks, euG ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
Re: [Ifeffit] Cadmium K-edge
Hi Bhoopesh and Scott, I should have given a description of my project. Yes Scott, the work is to investigate the binding mechanisms of aqueous cadmium onto sodium titanate nanotubes. Spectrum of Sample 1 and 2 obtained from merging 9 scans and 4 scans, respectively. A quick check in Athena and, indeed, the white line of Samples are higher than CdO. I'm not sure the reason behind it though. It is likely that cadmium binds to the surface of substrate rather than inside the bulk. The lack of distinct peaks after 1.8 Å means that there are not many scatters around the absorber? Bhoopesh, as requested, I have attached the real part of FT ( http://img585.imageshack.us/i/ftreal.jpg/). I haven't got a chance to interpret them. >From preliminary fitting of Sample 1, the major and minor peaks at 1.8 and 2.3 Å could be described by a Cd-O path (CdO). This interests me because Sample 2 does not have a peak at 2.3 Å, meaning there is another single scattering path for Sample 2?. The peaks at 3 Å were fitted with Cd-Ti path (CdTiO3). No multiple scattering paths used. The best fit goes something like this: Independent points = 13.166992187 Number of variables = 8.0 Chi-square =1534.709946959 Reduced Chi-square = 297.021921317 R-factor= 0.000128095 Measurement uncertainty (k) = 0.60423 Measurement uncertainty (R) = 0.004455442 Number of data sets = 1.0 Guess parameters +/- uncertainties (initial guess): amp = 0.9242390 +/- 0.0509920(1.) enot= 1.3950420 +/- 0.5425380(0.) delr=-0.0872060 +/- 0.0051060(0.) ss = 0.0113250 +/- 0.0008480(0.0030) amp_2 = 0.2441320 +/- 0.1905250(1.) enot_2 =22.5261260 +/- 4.5990590(0.) delr_2 = 0.2510860 +/- 0.0719080(0.) ss_2= 0.0274690 +/- 0.0128040(0.0030) Correlations between variables: amp_2 and ss_2 --> 0.9342 enot_2 and delr_2 --> 0.9133 amp and ss --> 0.8865 enot and delr --> 0.8632 amp_2 and delr_2 --> 0.3040 delr_2 and ss_2 --> 0.2888 All other correlations are below 0.25 k-range = 2.000 - 9.000 dk = 1.000 k-window= hanning k-weight= 3 R-range = 1.000 - 4.000 dR = 0.000 R-window= hanning fitting space = R background function = none phase correction= none R-factor for this data set = 0.00270 *** The above enot_2 is on the high side. I am not entirely familiar with the parameters yet. Are there other parameters I should worry about? Cheers, Alan J. DU Nanyang Technological University, Singapore ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
Re: [Ifeffit] N independent variables
Thank you once again Matt, I am sorry for sending just a portion of the log file. I thought that way it would be easier to look for the details. Won't happen again. Jesús 2016-05-23 16:31 GMT-03:00 Matt Newville : > Jesus, > > > On Mon, May 23, 2016 at 2:07 PM, Jesús Eduardo Vega Castillo < > jeve...@gmail.com> wrote: > >> Dear list, >> >> I made an EXAFS analysis in Artemis (in Demeter 0.9.22) using all the >> available variables. This is a fragment of the .log file I got: >> >> Independent points : 17.7666016 >> Number of variables : 17 >> Chi-square : 265.0947132 >> Reduced chi-square : 345.8050781 >> >> R-factor: 0.0026486 >> >> Number of data sets : 1 >> : k-range = 2.942 - 11.043 >> : dk= 1 >> : k-window = hanning >> : k-weight = 1,2,3 >> : R-range = 1.115 - 3.5 >> : dR= 0.0 >> : R-window = hanning >> : fitting space = r >> : background function = yes >> : phase correction = no >> : background removal = E0: 20002.215, Rbkg: 1.0, range: >> [2.25:17.4039986832903], clamps: 0/24, kw: 2 >> : epsilon_k by k-weight = 3.189e-004 >> : epsilon_r by k-weight = 2.339e-001 >> : R-factor by k-weight = 1 -> 0.00220, 2 -> 0.00224, 3 -> 0.00392 >> >> The problem is that when I use the Nyquist criterion >> >> Nind=2*deltak*deltar/pi + 1 >> >> for calculating the number of independent points the value I got is much >> lower and close to 13. >> >> I was not aware of this discrepancy and it caused a reviewer to think I >> made up the fit! >> >> > Sending the entire log file is always recommended. Otherwise, you are > selectively editing what you are telling us, and expecting us to guess what > you haven't told us. Sending the project file is often a good choice. > > Fortunately, you included an important clue. You have "background > function = yes", which means the fit will actually extend down to R=0, > using your Rmin as Rbkg in calculating how many variables are used for the > spline. With that included, the fit does contain approximately 18 > independent parameters, about 5 of which will be used for the background > subtraction. > > --Matt > > ___ > Ifeffit mailing list > Ifeffit@millenia.cars.aps.anl.gov > http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit > Unsubscribe: http://millenia.cars.aps.anl.gov/mailman/options/ifeffit > > ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit Unsubscribe: http://millenia.cars.aps.anl.gov/mailman/options/ifeffit
[Ifeffit] Artemis fit error - chi-square and R-factors are always equal to 0
Hello, I have recently installed Demeter suite on my LinuxMint 20 machine with all required dependencies met. Athena works well and Demeter passed all tests during installation. When running Artemis however, there is an issue with fits that persists with provided examples any any other projects I open (including the ones done by colleagues and just re-run on my machine). After the fit (which completes fine and returns expected fit that looks ok when comparing it to experiment), when inspecting the log file, chi-square, reduced chi-square and R values are equal to 0 (example log file attached bellow). No errors accompany the fit. I am using Larch installed with anaconda, and Artemis uses Feff6 executable. I have re-installed Demeter and tried to get it to work with Ifeffit but the error persists. I have found an existing git hub thread dealing with similar issue (https://github.com/bruceravel/demeter/issues/62) but no solution that I could discern. Could it be an issue with my perl version (5.30.0)? If someone has any ideas what the issue could be and how to fix it, I would appreciate the help. Please let me know if I can provide any additional information, and I apologize if there is something obvious I may have missed. Sincerely, Ava -- Ava Rajh Name: Fit 4(fzexv) Description : fit to cu010k Figure of merit : 4 Time of fit : 2021-03-26T12:12:21 Environment : Demeter 0.9.26 with perl 5.03 and using Larch X.xx on linux Interface : Artemis (Wx 0.9932) Prepared by : ava@ava-PC Contact : =*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*= Independent points : 25.401 Number of variables : 4 Chi-square : 0.000 Reduced chi-square : 0.000 R-factor: 0.000 Number of data sets : 1 Happiness = 100.00/100 color = #D8E796 * Note: happiness is a semantic parameter and should * *NEVER be reported in a publication -- NEVER!* guess parameters: ss_Cu1 = 0.00341875# +/- 0.3724 [0.00300] dr_Cu1 = -0.00471435# +/- 0.00045738 [-0.00504] dE0= 5.41536257# +/- 0.14032983 [5.36177] amp= 0.89986572# +/- 0.00826589 [0.9] set parameters: N1 = 1. Correlations between variables: All other correlations below 0.4 = Data set >> cu010k << : file= : name= cu010k : k-range = 3.000 - 22.950 : dk = 1 : k-window= Hanning : k-weight = 3 : R-range = 1 - 3 : dR = 0.0 : R-window= Hanning : fitting space = r : background function = no : phase correction= no : background removal = : user-supplied epsilon_k = 0 : epsilon_k by k-weight = 3 -> 2.602e-04 : epsilon_r by k-weight = 3 -> 3.592e-01 : R-factor by k-weight= 1 -> 0.00434, 2 -> 0.00233, 3 -> 0.00246 nameN S02 sigma^2 e0 delr Reff R = [atoms] Cu.1 12.000 0.000 0.0 0.000 0.0 2.55270 2.55270 nameei third fourth = [atoms] Cu.1 0.0 0.0 0.0 =*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*= ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit Unsubscribe: http://millenia.cars.aps.anl.gov/mailman/options/ifeffit
Re: [Ifeffit] Running (D)Artemis yields different result from that shown in (D)Artemis instruction videos
OK, you've convinced me. When I got into the lab this afternoon, I tried the same fit on a Windows computer. Much to my surprise, the result on Windows was quite different from the result on my linux computers at home. After a few hours of investigation, I found a problem in how Ifeffit had been compiled on the Windows machine that I use to build the Windows installer. I was able to come up with a short-term solution and then built a new installer package for 0.9.13 which i think works correctly. I will be announcing a new release shortly. B On Monday, October 22, 2012 06:41:26 AM Tsuei, Ku-Ding wrote: > Bruce, > > Perhaps you noticed the "Fit color" was red (large R-factor 0.074496, > poor fit, also seen in the attached figure in the last email) when you > loaded in the project file I sent you. When you hit Fit button again the > "Fit color" might turn to green indicating good fit as shown in your > result of a much smaller R-factor (0.004265). > > I did the following test on various versions of Demeter on my desktop > and notebook computers both installed with Windows 7 SP1. Of course I > uninstalled one version first before installing another. I tried to use > Uninstall within the Program menu or use the Program manager. I tried to > reboot or not to reboot after uninstallation or installation. Neither > shows any difference. > > Fit color > 0.9.10 green > 0.9.11 red > 0.9.12 red > 0.9.13 red > > Only version 0.9.10 yields good fit. The latter versions would not give > good fits even with repeated hitting the "Fit" button. I have no idea > what causes these results but perhaps this observation provides a clue. > > Ku-Ding > > On 2012/10/22 上午 01:00, ifeffit-requ...@millenia.cars.aps.anl.gov wrote: > > Send Ifeffit mailing list submissions to > > > > ifeffit@millenia.cars.aps.anl.gov > > > > To subscribe or unsubscribe via the World Wide Web, visit > > > > http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit > > > > or, via email, send a message with subject or body 'help' to > > > > ifeffit-requ...@millenia.cars.aps.anl.gov > > > > You can reach the person managing the list at > > > > ifeffit-ow...@millenia.cars.aps.anl.gov > > > > When replying, please edit your Subject line so it is more specific > > than "Re: Contents of Ifeffit digest..." > > > > Today's Topics: > > 1. Re: Running (D)Artemis yields different result from that > > > >shown in (D)Artemis instruction videos (Ravel, Bruce) > > > > -- > > > > Message: 1 > > Date: Sun, 21 Oct 2012 12:36:10 + > > From: "Ravel, Bruce" > > To: XAFS Analysis using Ifeffit > > Subject: Re: [Ifeffit] Running (D)Artemis yields different result from > > > > that shown in (D)Artemis instruction videos > > > > Message-ID: > > <47ced3cd722c2a439c0d1d1056b2132517c3b...@ex10-mb1.bnl.gov> > > > > Content-Type: text/plain; charset="us-ascii" > > > > > > Ku-Ding, > > > > I don't know what to tell you. On the computer I am sitting in front of > > right now, I opened your two project files and hit the fit buttons, I get > > the same fit with only numerical differences. Here I am cutting and > > pasting from the two log files:> > > old artemis: > >Chi-square =4334.684537717 > >Reduced Chi-square = 691.819976095 > >R-factor= 0.004250325 > > > >amp = 0.8649100 +/- 0.0412220(1.) > >enot= 5.6049380 +/- 0.2950270(0.) > >delr=-0.0226780 +/- 0.0023790(0.) > >ss = 0.0082230 +/- 0.0003250(0.0030) > > > > new artemis: > >Chi-square : 4348.7359268 > >Reduced chi-square : 694.0625918 > >R-factor: 0.0042652 > > > >amp= 0.86526150# +/- 0.04129645 [1.0] > >enot = 5.61081742# +/- 0.29527844 [0] > >delr = -0.02266589# +/- 0.00238341 [0] > >ss = 0.00822546# +/- 0.00032571 [0.00300] > > > > I don't acknowledge that there is a problem. > > > > B > > > > > > > > From:ifeffit-boun...@millenia
Re: [Ifeffit] k-range question & R-factor
Hi Chris, I don't see a reason to think that data is a glitch. For one thing, it's not consistent across datasets. The features also look smooth, and not so glitch-like. The spike around 8.2 inverse angstroms in some of the datasets looks a bit more like a glitch, but it's fairly modest and narrow enough not to mess you up too much. The spacing of those features look OK--there's a double feature in some of the datasets around 6-7 inverse angstroms; it's plausible there would be another reature like that above it. In fact, I can make an argument that there's some kind of beating going on that gives a shoulder at 3.5-5, a double peak at 5-7, and two peaks at 7-8 inverse angstroms. So I would recommend including that data and seeing what it does to your fits. If that range is garbage, your fits will probably reject it. As for your second question, R-factors are always a kind of average across the data, by definition. So "total" mismatch doesn't really make sense. Off-hand, though, I don't recall how ifeffit weights the data for the purposes of calculating R-factors for multiple datasets, and that may be your question. --Scott Calvin Sarah Lawrence College On Jan 15, 2013, at 9:21 AM, Christopher Patridge wrote: > Hello Users, > > I was looking for an opinion about the chi(k) signal in a set of data I > am analyzing. Brief background, this is a set of in-situ XAS data > collected at the Fe K edge from a working electrochemical cell at a > range of potentials during charge; I did not collect the data. I suspect > the feature at ~ 8 angstroms-1, although present in all the spectra is > noise or glitch and wondered if I am being overly cautious? > > My conservative range ( k = 2-7 and R = 1-2) really constrains the model > Nidp = 3.31. Luckily, multiple datasets ( 8 ) to the rescue to give me > some flexibility. In a multiple dataset fitting, is the R-factor of the > whole set just the average or total mismatch across all the datasets or > it calculated another way? > > Working towards happiness, > > Chris Patridge > > -- > > Christopher J. Patridge, PhD > NRC Post Doctoral Research Associate > Naval Research Laboratory > Washington, DC 20375 > Cell: 315-529-0501 > > ___ > Ifeffit mailing list > Ifeffit@millenia.cars.aps.anl.gov > http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
Re: [Ifeffit] Chi in arthemis
Hi Scott, > Is this the most recent IXAS report on error reporting standards? > > http://www.i-x-s.org/OLD/subcommittee_reports/sc/err-rep.pdf Yes. To be clear, the main value of reduced chi-square is that it can be used (even if with some inherent uncertainty) to compare two models with different number of variables. Many analysis programs report only a value like R-factor (ie, the misfit not scaled by the measurement uncertainty or number of free parameters in the data). Again, this is an OK measure of the misfit, though it too is scaled somewhat arbitrarily, and cannot be used to compare models with different number of variables. > ... In such cases I have become convinced that the R-factor alone > provides as much meaningful information as the chi-square values, > and that in fact the chi-square values can be confusing when listed > for fits on different data. For those working with dilute samples, > on the other hand, I can see that chi-square might be a meaningful > quantity. > > ... I strongly agree that the decision of which measurements > of quality of fit to produce should not be dependent on what "looks > good"! That would be bad science. The decision of what figures of > merit to present should be made a priori. The subcommittee that looked into agreed (after some debate) on wording and recommendations of such topics also thought it should be done a priori, though they also thought is should be done without regard to quality of the data or type of samples. You're free to disagree with this report. --Matt ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
[Ifeffit] Questions on Correlated Debye in FEFF6
Hi Everyone, I have just recently begun learning about EXAFS and running EXAFS simulations using FEFF6. I have a few very basic questions about the underlying calculations for the correlated Debye model implemented in FEFF6 (called by "DEBYE" keyword). For the questions below, I am assuming I input a single crystallographic structure and want the correlated Debye model to simulate the influence of a thermal distribution on the EXAFS spectrum. I would appreciate any insight you can give me into the questions below. I would also welcome any and all references for the original papers where that is appropriate. 1. Are the Debye-Waller factors calculated for each path individually? (It seems like they should be since the paths will have different levels of influence from the thermal distribution of atomic positions) 2. Assuming the DW factors are calculated path-by-path, is the magnitude of the DW factor determined by assuming the total path length R is the appropriate length to use for the correlation term in the Debye spectral density? It seems like it would not be reasonable to treat all paths of the same R as having the same Debye-Waller factor since a single scattering path and multiple scattering paths are perturbed by a different set of relative atomic motion that are likely to have different correlations. I couldn't locate a clear statement about how this calculations is actually done within the code. 3. Is the C1 shift that results from the vibrational motion normal to the bond axis along a path incorporated in the calculation? (Presumably using \Delta C1 = sigma_perp^2/(2)) And is this formula still appropriate in multiple-scattering paths? 4. Assuming the C1 shift is incorporated, does the correlated Debye model assume that the perpendicular and parallel displacements have the same spectral density? Thank you for the assistance! Doran Doran I. G. Bennett The Dow Chemical Company Core R&D, Inorganic Material and Heterogeneous Catalysis Phone: (610)-244-7062 Alternate Phone: (630)-222-2906 ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
Re: [Ifeffit] Query regarding error bars
On Friday 09 January 2009 09:12:16 am Bindu R. wrote: > Could any tell me in a simple language about the error bars returned by the > EXAFS fitting program? > what do they exactly represent? > How is it determined? > How is the number of iterations decided. > In addition to R-factor what are the other parameters which determines a > good fit. For a R-factor ~0.001, if the value of chi2~10,000 and reduced > chi2 ~ 500, can one consider the fit to be good even if one gets a good > match to the experimental spectra. I believe that most of these questions are answered at http://cars9.uchicago.edu/iffwiki/FAQ/FeffitModeling The number of iterations is determined from the data. That is, when the fit converges to within some tolerance, the fit stops and the error bars are evaluated. There is a hard-wired default for that tolerance and long experience suggests it is reasonable. There is also a hard-wired upper limit to the number of iterations, but a decent fit never reaches that number. The error bars are the diagonal elements of the covariance matrix evaluated during the fit. Because uncertainty is so hard to properly evaluate (as discussed in the links in the FAQ), the error bars are rescaled under the assumption that the fit performed was, in fact, a good fit. Thus the error bars are a reasonable (although probably conservative) estimate of measurement uncertainty if you believe that the fit is indeed a good fit. Again, see the FAQ for some hints about how to decide if a a fit is a good fit. If you have additional specific questions, let us know so we can answer them here and update the FAQ as needed. Regards, B -- Bruce Ravel bra...@bnl.gov National Institute of Standards and Technology Synchrotron Methods Group at NSLS --- Beamlines U7A, X24A, X23A2 Building 535A Upton NY, 11973 My homepage:http://xafs.org/BruceRavel EXAFS software: http://cars9.uchicago.edu/~ravel/software/exafs/ ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
[Ifeffit] Trouble with fitting with Arthemis
Hi all, Please, help me. When I try to do any fit in Arthemis, setting all parameters unless one, been this one any of the parameters, the fit gives for the answer -1. +/- 0.00 like example down. What is happening? Independent points = 8.239257812 Number of variables = 1.0 Chi-square = 0.12000E+37 Reduced Chi-square = 0.165762849E+36 R-factor= NaN Measurement uncertainty (k) = 0.000437667 Measurement uncertainty (R) = 0.000724906 Number of data sets = 1.0 Guess parameters +/- uncertainties (initial guess): * amp =-1.000 +/- 0.000(1.)* Set parameters: enot= 0 delr= 0 ss = 0.003 c3 = 0.0001 c4 = 0.1 -- Kleper de Oliveira Rocha Chemical Engenieer Doctorated Tels. 55 016 3351-8694 ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
[Ifeffit] "FEFF+IFEFFIT" and "cumulant expansion+ratio method" approaches
Dear all, I'm stuck on a peculiar situation and would appreciate any kind of help available. I need to "translate" EXAFS analysis results obtained with IFEFFIT/FEFF into the "language" of the cumulant expansion/ratio method approach. More specifically, I have to relate my mean interatomic distance R obtained with IFEFFIT to the first cumulants (mean interatomic distances) that show up in the ratio method formalism. I'm saying the cumulantS because the ratio method makes a distinction between the so called "effective P(r,lambda)" and "real rho(r)" distributions of interatomic distances, which are related by: P(r,lambda)=rho(r)*[[exp(-2r/lambda)]/r^2] . For the second cumulant (Debye-Waller factor or sigma^2) and higher terms, the difference between "effective" and "real" values is not significant unless the disorder in the sample is really big. But for the first cumulant it is significant (at least at not very low temperatures), being the "real" first cumulant bigger than the "effective" one by a term like [(2*sigma^2)/r]*[1+(r/lambda)]. My dilemma is: how my mean interatomic distance R from IFEFFIT relates to the "effective" and "real" first cumulants? Should it be the same as one of them? Which one? Or it doesn't correspond exactly to any of them? Any comments will be welcome... Regards, Leandro ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
Re: [Ifeffit] third cumulant
On May 6, 2012 11:01 PM, "JeongEunSuk" wrote: > > Hello > I measured temperature-dependent EXAFS at Pt L3 edge with Pt nanoparticles in room and high temperature(400 C). I have some questions about thermal vibration in EXAFS fit. I read that third and fourth culmulants related with phase and amplitude in anharmonic term, respectively. especially, I concerned third culmulant to relate with phase. > As you know, the phase also relates with bonding length. So that, the bonding length between Pt-Pt pair considerably correlated with third culmulant. So I can't decide exact bonding length and third culmulant because their correlation. I think that the relation of both bonding length and third culmulant is similar to that of number and debye-waller factor. > Is it right to find bonding length and third culmulant like finding number and debye-waller factor using k-weight? Yes, c3 and R are correlated. And, as it turns out, in almost exactly the same way that N and sigma2 are. That doesn't mean they can't be determined accurately, though. It will tend to make for larger uncertainties, but this is taken into account in ifeffit (at least to first order, ie assuming that the errors are normally distributed and a map of chi-square would be ellipsoidal). Many people vary the k-weighting to try to "break" these correlations. I think it doesn't really reduce the correlation that much (certainly not below 50%), but it can't hurt. You might also consider asserting some mathematical relationship for R and c3 with temperature, and fit the parameters of those relationships. FWIW, my experience is that c3 is rarely significant (ie different from 0), until you get to very high temperature. For 400C for Pt, I'd expect that it would start to be noticeable. --Matt ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
[Ifeffit] Question on (Combo-) LCF plot output
Dear Mailing list, I am a relatively new user in terms of XAS data handling and I encountered a strange problem during LCF in Athena. I am working on LCF-combo fittings for Mn minerals as described in Manceau et al. 2012*. Fitting f.ex. a cryptomelane sample of myself with the open source monovalent manganese mineral standards of Manceau et al. 2012 in a fit range of -20 to +30 k, gives the following result shown below (I´ll attach the Athena project): " LCF fit of Cryptomelane_T_20K_ecd as flattened mu(E) from 6536.79 to 6586.79 Fit included 100 data points and 6 variables, and approximately 41.333 measurements Weights sum to 1: no Weights forced between 0 and 1: no Overall e0 shift used: yes Noise added to data: 0 R-factor = 0.0003537 Chi-square = 0.00815 Reduced chi-square = 0.858 .standard weight e0 . Manganosite.dat 0.042 (0.006)1.631 (0.044) . Groutite.dat 0.030 (0.029)1.631 (0.044) . Ca2Mn3O8.dat 0.288 (0.026)1.631 (0.044) . Ramsdellite.dat 0.584 (0.022)1.631 (0.044) . Mn2O3.dat 0.044 (0.025)1.631 (0.044) . sum ... 0.988 " Note that the box “all standards share an E0” is checked before clicking on “Fit this group”. Optically, the fit itself “looks” good compared to the data, yet, it is somewhat shifted on the x-axis compared to the data. I was wondering why, as this was not the first sample where this was the case. When I now uncheck the “All standards share an E0” box, leave everything else just the way it is and just click “Fit this group” again, the fit suddenly is shifted perfectly on my data. The strange thing is: Nothing else in the output-results changes – weights, R-factor, chi-square etc. just stay the same. Only slight changes in the numbers in brackets after the reported weights. The "new" result is: " LCF fit of Cryptomelane_Mikon_T_20K_ecd_reb-a-m as flattened mu(E) from 6536.79 to 6586.79 Fit included 100 data points and 5 variables, and approximately 41.333 measurements Weights sum to 1: no Weights forced between 0 and 1: no Overall e0 shift used: no Noise added to data: 0 R-factor = 0.0003537 Chi-square = 0.00815 Reduced chi-square = 0.849 .standard weight e0 . Mn2O3.dat 0.044 (0.024)1.631 (0.000) . Manganosite.dat 0.042 (0.006)1.631 (0.000) . Ca2Mn3O8.dat 0.288 (0.024)1.631 (0.000) . Ramsdellite.dat 0.584 (0.019)1.631 (0.000) . Groutite.dat 0.030 (0.026)1.631 (0.000) . sum ... 0.988 " Can anybody tell me, what is actually happening? I exported both data to excel to replot the fits to exclude a simple plot-bug, but the data behind show that this is real. So, I am changing the data behind the plot, but actually not the output data … what is going on here? You find the project attached – I hope someone can tell me, how to cope with that! Thank you very much, Teresa *Manceau, A., Marcus, M. A., & Grangeon, S. (2012). Determination of Mn valence states in mixed-valent manganates by XANES spectroscopy. American Mineralogist, 97(5-6), 816-827. -- Teresa Zahoransky Soil Mineralogy Gottfried Wilhelm Leibniz Universität Hannover Institute of Mineralogy Callinstr. 3, Room 325 D-30167 Hannover, Germany Phone: +49 (0)511 762-8058 Email: t.zahoran...@mineralogie.uni-hannover.de LCF-combo_question.prj Description: Binary data ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit Unsubscribe: http://millenia.cars.aps.anl.gov/mailman/options/ifeffit
Re: [Ifeffit] Running (D)Artemis yields different result from that shown in (D)Artemis instruction videos
Dr. Ravel, I am a beginner for xafs analysis. I installed the Demeter on my laptop. I found there was always a black command widow when I start athena or artermis. If I close that window, the program was also closed. My operation system is windows 7. Why? Shaofeng > -原始邮件- > 发件人: "Bruce Ravel" > 发送时间: 2012年10月23日 星期二 > 收件人: "XAFS Analysis using Ifeffit" > 抄送: > 主题: Re: [Ifeffit] Running (D)Artemis yields different result from that shown > in (D)Artemis instruction videos > > > OK, you've convinced me. > > When I got into the lab this afternoon, I tried the same fit on a > Windows computer. Much to my surprise, the result on Windows was > quite different from the result on my linux computers at home. > > After a few hours of investigation, I found a problem in how Ifeffit > had been compiled on the Windows machine that I use to build the > Windows installer. > > I was able to come up with a short-term solution and then built a new > installer package for 0.9.13 which i think works correctly. > > I will be announcing a new release shortly. > > B > > > > On Monday, October 22, 2012 06:41:26 AM Tsuei, Ku-Ding wrote: > > Bruce, > > > > Perhaps you noticed the "Fit color" was red (large R-factor 0.074496, > > poor fit, also seen in the attached figure in the last email) when you > > loaded in the project file I sent you. When you hit Fit button again the > > "Fit color" might turn to green indicating good fit as shown in your > > result of a much smaller R-factor (0.004265). > > > > I did the following test on various versions of Demeter on my desktop > > and notebook computers both installed with Windows 7 SP1. Of course I > > uninstalled one version first before installing another. I tried to use > > Uninstall within the Program menu or use the Program manager. I tried to > > reboot or not to reboot after uninstallation or installation. Neither > > shows any difference. > > > > Fit color > > 0.9.10 green > > 0.9.11 red > > 0.9.12 red > > 0.9.13 red > > > > Only version 0.9.10 yields good fit. The latter versions would not give > > good fits even with repeated hitting the "Fit" button. I have no idea > > what causes these results but perhaps this observation provides a clue. > > > > Ku-Ding > > > > On 2012/10/22 上午 01:00, ifeffit-requ...@millenia.cars.aps.anl.gov wrote: > > > Send Ifeffit mailing list submissions to > > > > > > ifeffit@millenia.cars.aps.anl.gov > > > > > > To subscribe or unsubscribe via the World Wide Web, visit > > > > > > http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit > > > > > > or, via email, send a message with subject or body 'help' to > > > > > > ifeffit-requ...@millenia.cars.aps.anl.gov > > > > > > You can reach the person managing the list at > > > > > > ifeffit-ow...@millenia.cars.aps.anl.gov > > > > > > When replying, please edit your Subject line so it is more specific > > > than "Re: Contents of Ifeffit digest..." > > > > > > Today's Topics: > > > 1. Re: Running (D)Artemis yields different result from that > > > > > >shown in (D)Artemis instruction videos (Ravel, Bruce) > > > > > > -- > > > > > > Message: 1 > > > Date: Sun, 21 Oct 2012 12:36:10 + > > > From: "Ravel, Bruce" > > > To: XAFS Analysis using Ifeffit > > > Subject: Re: [Ifeffit] Running (D)Artemis yields different result from > > > > > > that shown in (D)Artemis instruction videos > > > > > > Message-ID: > > > <47ced3cd722c2a439c0d1d1056b2132517c3b...@ex10-mb1.bnl.gov> > > > > > > Content-Type: text/plain; charset="us-ascii" > > > > > > > > > Ku-Ding, > > > > > > I don't know what to tell you. On the computer I am sitting in front of > > > right now, I opened your two project files and hit the fit buttons, I get > > > the same fit with only numerical differences. Here I am cutting and > > > pasting from the two log files:> > > > old artemis: > > >Chi-square =4334.684537717 > > >Reduced Chi-square = 691.819976095 > > >R-factor= 0.004250325 > > > > > >
Re: [Ifeffit] Third cumulant in DWF
Thanks, Bruce. Does the math expression in IFEFFIT include the term -4k*sigma2*(1/labmda +1/R) in the phase? If yes, the 1st cumulant is sigma1= R+dR. If no, sigma1= R+dR+2*sigma2*(1/labmda +1/R). It this correct? Yuan On 4/1/11 2:18 PM, "Bruce Ravel" wrote: > On Friday, April 01, 2011 05:03:17 pm Ping, Yuan wrote: >> Dear IFEFFIT experts: >> >> Is it possible to add a k^3 term in the phase for fitting to take into >> account anharmonic effect? The fitted coefficient will be proportional to >> the 3rd cumulant of Debye-Waller factor. I work with high-temperature >> high-pressure systems where anharmonic effect is not negligible. >> >> Thanks. >> Yuan Ping > > > Hi Yuan, > > Here is the relevant page from the Ifeffit reference manual: > >http://cars9.uchicago.edu/~ifeffit/refman/node51.html > > You want to use the "3rd" path parameter, which adds a term > proportional to C3*k^3 to the sine function in the exafs equation. > > See the attached figure for the place in Artemis where this parameter > is introduced. > > HTH, > B ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
Re: [Ifeffit] a question
Are you determining bond length from the magnitude of chi(R) or are you fitting ab initio data to the curves? In my experience the |chi(R)| peaks are usually closer than the actual bond distances due to phase shift. Dr Somaditya Sen wrote: > Hi All > I am having problems in comparing the real bond length as obtained > from EXAFS data and Reitveld analysis of XRD data of te same sample. > The bond lengths as observed from the XAFS data seems to be much > smaller that that from XRD. Is there some multiplication factor known > in literature to address this issue? > > S Sen > > > > > > ___ > Ifeffit mailing list > Ifeffit@millenia.cars.aps.anl.gov > http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit > -- Jason Gaudet Environmental Catalysis and Nanomaterials Laboratory Department of Chemical Engineering Virginia Tech 147B Randolph Hall Blacksburg, VA 24061 540-231-9371 jgau...@vt.edu ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
[Ifeffit] save Artemis project and cannot find Path List information when reopen
Hi all, I encountered a serious problem with saving an Artermis project on my windows 8 64bit desktop. When I am ready to finish my fitting work, I click to save the log file, and go to main window to choose -File-'save project as...', and then close Artemis. But when I reopen this saved project, the Path Page lost all information for each path, and the 'Include path' button has been surprisingly unchecked for all path. The GDS page have all information there. This happened to me several times, but it seems sometime the PathPage data is saved and sometime is not, although I think I was doing the exact something. I attached one of my artemis project file and the most recent log file I saved before I close the program. Can anyone have a look and tell me what I did wrong? As my work is proceeding, this would be a very serious problem if I cannot save my 'hardwork'. Best, Yanyun - Attachments (links will expire on 28/02/15): 1. CoedgeforGa0.15 fitting.fpj (7.7 MB) [application/zip] Download link: https://webmail.physics.utoronto.ca/imp/attachment.php?id=53ffbffa-2424-4131-b215-2fa28e014128&u=huyanyun Name: Fit 102(arjdv) Description : fit to merge_Co_Ga0.15Co4Sb12 Figure of merit : 102 Time of fit : 2014-08-28T19:06:27 Environment : Demeter 0.9.18 with perl 5.012003 and using Ifeffit 1.2.11d on Windows 8 Interface : Artemis (Wx 0.99) Prepared by : Contact : =*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*= Independent points : 31.1660156 Number of variables : 17 Chi-square : 4855.1094586 Reduced chi-square : 342.7293593 R-factor: 0.0266456 Measurement uncertainty (k) : 0.0007222 Measurement uncertainty (R) : 0.0017191 Number of data sets : 1 Happiness = 87.35/100 color = #F6EC91 An R-factor of 0.02665 gives a penalty of 6.64560. Penalty of 2 : sigma2 for " Sb1.4 " is suspiciously large. Penalty of 2 : sigma2 for " Sb1.1 Sb1.1 " is suspiciously large. Penalty of 2 : sigma2 for " Ga1.1 " is negative. * Note: happiness is a semantic parameter and should * *NEVER be reported in a publication -- NEVER!* guess parameters: amp= 0.62612908# +/- 0.07447453 [1.0] enot = -2.22915585# +/- 0.91740694 [-1.97263] ss = 0.00035684# +/- 0.00105886 [0.00300] ss2= 0.00548989# +/- 0.00249812 [0.00300] alpha = -0.00893872# +/- 0.00283575 [-0.00642] ss3= 0.00847101# +/- 0.00654134 [0.00300] ss1= 0.01741252# +/- 0.01710780 [0.00300] ss4= 0.10587548# +/- 1.36365129 [0.00300] ss5= 0.00414090# +/- 0.00501336 [0.00300] ss6= 0.00539655# +/- 0.01054992 [0.00300] ss7= 0.09300107# +/- 0.40650454 [0.00300] ss8= 0.00405116# +/- 0.00375482 [0.00300] ss9= 0.01144330# +/- 0.06295943 [0.00300] Nlong = 5.63811438# +/- 0.16088706 [5] R1 = 2.07875206# +/- 0.02982666 [2.1] delr_ga2 = -0.00657662# +/- 0.01562471 [0] ssga2 = -0.0125# +/- 0.00190640 [0.003] def parameters: Nshort = 0.36188562# [6 - Nlong] Correlations between variables: ssga2 & ss --> 0.9421 delr_ga2 & alpha --> 0.8570 alpha & enot --> 0.8492 ss & amp--> 0.8341 ssga2 & amp--> 0.7887 ss6 & ss5--> 0.7622 ss9 & ss8--> -0.7587 delr_ga2 & enot --> 0.7302 ssga2 & r1 --> 0.6756
[Ifeffit] Writing a paper
Hello Everyone, I am in the process of fitting XAFS data for a paper and I was wondering what type of information should should be included. I remember coming across a website that had this information on it awhile ago but I can't seem to find my way back. We would like to publish a qualitative XANES paper and an EXAFS paper. Any suggestions on the type of information (plots, tables, R-factor, etc.) that should be included in each paper separately would be appreciated. Thanks, Matthea Peck ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
[Ifeffit] (no subject)
Respected Sir, I am new in the field of EXAFS. I have few questions regarding to IFEFFIT i.e., fitting of theoretical models to the experimental EXAFS data. 1. *1*.What is the ideal value of R- factor for any fit. 2. *2. * Can we use (fit) the theoretical model generated from square pyramidal structure to EXAFS data of octahedral structure by assigning degeneracy of 2 for the apical atom. OR using octalhedral for square planar by not using apical path Yours faithfully Davood Ah. Dar EXAFS research scholar India ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
Re: [Ifeffit] problem of overestimated E0 (Edge-energy)
I think we'll need more information to help out: at a minimum, the
feff.inp file. Also, are you fitting just the nearest neighbor
scattering path?
To begin to answer your question, while it is often the case that Eo
falls below the white line peak, this is not categorically true. A
relevant example might be PtO2.
Jeremy
Chemical Sciences and Engineering Division
Argonne National Laboratory
Argonne, IL 60439
Ph: 630.252.9398
Fx: 630.252.9917
Email: kr...@anl.gov
From: ifeffit-boun...@millenia.cars.aps.anl.gov
[mailto:ifeffit-boun...@millenia.cars.aps.anl.gov] On Behalf Of
JeongEunSuk
Sent: Thursday, January 12, 2012 3:47 PM
To: ifeffit
Subject: [Ifeffit] problem of overestimated E0 (Edge-energy)
Hello all
I want to understand EO(edge-energy), precisely. (In Artemis, EO is
writed as Enor)
Generally, EO is energy when electrons start to go out from core atom in
XAFS.
As you know, the experiments show that to find EO is not easy in XAFS.
To remove background, sometimes I chose EO, the value of the maximum
derivative in Athena.
and when fitting, the E0 is correted by theoritical FEFF.
This is my question.
The attached file is the figure of Pt foil(Pt L3 edge measurement).
I think edge-enegy has to be in range between A and C because electrons
start to move to continum state in that range.
However, fitted E0 is shifted to C (about 11573eV). and then when
removing background I chose E0=11563eV(This is Pt L3 edge).
Fitted E0 is overestimated value, compared with whit line(B).
That means the calculated EO obtained from FEFF8.0 (using auto-self
consistency field potential) is larg! er than that of experiment.
Do I need to change SCF potential in FEFF8.0?
This is fitting parameters and results(in my case, I used Linux version)
To remove background
k -range = 2.5 ~ 15, EO=11563eV, Rbkg=1.3, kweight =1
To fit data
k -range = 3.0~13.5, R -range =2.3~13.5
1. fitting parameters
set macc = 0.0
set so2 = 0.89// reduction factor
guess ePt = 0.0 // energy shift
set npt1=1.0// the number of Pt (1.0 means 12 Pt
atoms around core Pt)
gu! essdpt1 = 0.0042 // effective bonding length
guesssigpt1=0.005100 //Debye waller factor
2. fitting results
fit results, goodness of fit, and error analysis:
independent points in data= 8.152
number of variables in fit= 3
degrees of freedom in fit = 5.152
r-factor of fit = 0.002700
chi-square=1267.097168
! ;reduced chi-square &nb! sp; = 245.926361
feffit found the following values for the variables:
variablebest fit valueuncertainty initial guess
ept= 10.7581980.8604944.00
dpt1 =0.0064620.0029300.004200
sigpt1 = &nbs! p; 0.0051140.98
0.005100
correlation between variables
variable #1variable #2 correlation
eptdpt1 0.926524
all other correlations are less than0.25000
-
Because the correlation between E0 and effective bonding length is big,
I checked the fit as set bonding and the rest of parameters is
variables, and then the result is not changed. That means EO still is
big.
&! nbsp;
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[Ifeffit] questions regarding to ifeffit fitting
Respected Sir, I am new in the field of EXAFS. I have few questions regarding to IFEFFIT i.e., fitting of theoretical models to the experimental EXAFS data. 1. What is the ideal value of R- factor for any fit. 2. * * Can we use (fit) the theoretical model generated from square pyramidal structure to EXAFS data of octahedral structure by assigning degeneracy of 2 for the apical atom. OR using octalhedral for square planar by not using apical path Yours faithfully Davood Ah. Dar EXAFS research scholar India ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
[Ifeffit] questions related to ifeffit fitting
Respected Sir, I am new in the field of EXAFS. I have few questions regarding to IFEFFIT i.e., fitting of theoretical models to the experimental EXAFS data. 1.What is the ideal value of R- factor for any fit. 2. ** Can we use (fit) the theoretical model generated from square pyramidal structure to EXAFS data of octahedral structure by assigning degeneracy of 2 for the apical atom. OR using octalhedral for square planar by not using apical path Yours faithfully Davood Ah. Dar EXAFS research scholar India ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
[Ifeffit] Questions about Athena and XANES
Hi all, Could someone please answer my questions? I would really appreciate your help. 1. For linear combination fitting, there are three indicators for the goodness of fitting: R-factor, chi-square and reduced chi-square. Could anyone tell me how they work? 2. Since TEY is sensitive for the surface and FY for the bulk (and surface?), species detected by TEY should be also detected by FY, right? 3. How to calculate the maximum analysis depths for TEY and FY? Thank you in advance. Jenny Cai ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
Re: [Ifeffit] Consistency criterion
Hi Juan, They're consistent. The higher r-factor on the kwt-1 data might be a clue about how reliable part of your data range is...since it's the kwt-1 that's higher, it may be that the low end of the k-range is not being fit very well (look at the k-space and q-space fits to help confirm this). That could be just because of glitchy data, iffy background subtraction, or that your model doesn't do as well with low-Z scatterers like oxygen as it does with the higher-Z contributions (the low-Z scatterers have most of their contributions at low k). Aside from looking at the k- and q-space fits, I'd try increasing kmin and see if that improves the fit. If it does, you might want to do it on the kwt-3 fit too, because that would suggest you're not fitting that low-k data very well, and the problem is just less emphasized with kwt-3. Of course it would be even better to find the source of the problem and address it. Having said that, I should emphasize that these are non-linear fits. Sometimes it's hard to come up with a simple explanation for why one fit is closer than another. Nevertheless, your fits are consistent. They're not equally "good"...but that's a different statement. In your situation, I would be comfortable publishing the kwt-3 fit and saying that other kwts gave consistent results. I would be more comfortable if I could figure out what was troubling the kwt-1 fit, though...especially if I had a mix of scatterers with substantially different atomic number (like transition metals with oxygens). --Scott Calvin Sarah Lawrence College At 08:03 AM 9/28/2006, you wrote: Hi all, Scott answered my question about consistency but now I have a new doubt. I have two fits (one in k1 and other in k3 weights) with fitted parameters that have uncertainty ranges overlaped, then... in principle, they are consitent, right? But the fit in k1 weight have a R-factor too high (0.06) and therefore is not a good fit. So I do not know if I can say that they are consistent even so. ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
Re: [Ifeffit] Trouble with fitting with Arthemis
Hi Kleper, It looks a little to me like you don't actually have any paths included in the fit, or perhaps the path is defective (all zeroed out, or something like that). If you attach the project file, it will probably be easy to tell. --Scott On Jan 13, 2009, at 5:13 PM, Kleper Oliveira Rocha wrote: > Hi all, > > Please, help me. When I try to do any fit in Arthemis, setting all > parameters unless one, been this one any of the parameters, the fit > gives for the answer -1. +/- 0.00 like example down. What is > happening? > > > Independent points = 8.239257812 > Number of variables = 1.0 > Chi-square = 0.12000E+37 > Reduced Chi-square = 0.165762849E+36 > R-factor= NaN > Measurement uncertainty (k) = 0.000437667 > Measurement uncertainty (R) = 0.000724906 > Number of data sets = 1.0 > > Guess parameters +/- uncertainties (initial guess): > amp =-1.000 +/- 0.000(1.) > Set parameters: > enot= 0 > delr= 0 > ss = 0.003 > c3 = 0.0001 > c4 = 0.1 > > -- > Kleper de Oliveira Rocha > Chemical Engenieer Doctorated ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
Re: [Ifeffit] Trouble with fitting with Arthemis
Hi Kleper, But your reduced chi-square is only 10^35. That seems like a pretty good fit... ;-) There is obviously a numerical problem, corrupted data, corrupted project file -- something like that. Can you send me the project file? B > Please, help me. When I try to do any fit in Arthemis, setting all > parameters unless one, been this one any of the parameters, the fit gives > for the answer -1. +/- 0.00 like example down. What is happening? > > > Independent points = 8.239257812 > Number of variables = 1.0 > Chi-square = 0.12000E+37 > Reduced Chi-square = 0.165762849E+36 > R-factor= NaN > Measurement uncertainty (k) = 0.000437667 > Measurement uncertainty (R) = 0.000724906 > Number of data sets = 1.0 > > Guess parameters +/- uncertainties (initial guess): > * amp =-1.000 +/- 0.000(1.)* > Set parameters: > enot= 0 > delr= 0 > ss = 0.003 > c3 = 0.0001 > c4 = 0.1 -- Bruce Ravel bra...@bnl.gov National Institute of Standards and Technology Synchrotron Methods Group at NSLS --- Beamlines U7A, X24A, X23A2 Building 535A Upton NY, 11973 My homepage:http://xafs.org/BruceRavel EXAFS software: http://cars9.uchicago.edu/~ravel/software/exafs/ ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
[Ifeffit] Data being overwritten in Artemis history window
?Dear All, Sorry... another bug report! Hopefully the last one for a while! In the history window some, but not all, data from previous fits seems to get overwritten when running a new fit. Specifically I've noticed this happening with the information in the "Data set" section. To reproduce run a QFS fit with some R-space fitting windows (say 2-4); at this point the log will be displayed correctly in the history window. Now change the R window (say 1.5-3.5) and run the fit again. When you go to the history window the R window information will be displayed correctly for the most recent fit but, for the previous fit it will have been overwritten by the newer fit. Some of the other info, such as R-factor by k-weight seems to get overwritten too. A video of this behaviour can be found here: https://wwwa-e.ucl.ac.uk/cgi-bin/dropbox/dropbox.cgi?state=pickup_info&id=29d3e5c2 password: 54c8545f System info: Win 8.1 Enterprise x64 running Demeter 0.9.22 pre release x64; log attached. All the best, Ian Ian Godfrey PhD Student, UCL/JAIST Programme Industrial Doctorate Centre in Molecular Modelling and Materials Science, Department of Chemistry, University College London and School of Materials Science, Japan Advanced Institute of Science and Technology i.godf...@ucl.ac.uk<mailto:i.godf...@ucl.ac.uk> i.godf...@jaist.ac.jp<mailto:i.godf...@jaist.ac.jp> dartemis.log Description: dartemis.log ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
Re: [Ifeffit] Data being overwritten in Artemis history window
On 03/09/2015 04:17 AM, Godfrey, Ian wrote: In the history window some, but not all, data from previous fits seems to get overwritten when running a new fit. Specifically I've noticed this happening with the information in the "Data set" section. To reproduce run a QFS fit with some R-space fitting windows (say 2-4); at this point the log will be displayed correctly in the history window. Now change the R window (say 1.5-3.5) and run the fit again. When you go to the history window the R window information will be displayed correctly for the most recent fit but, for the previous fit it will have been overwritten by the newer fit. Some of the other info, such as R-factor by k-weight seems to get overwritten too. Ian, I now understand what the problem is. Unhappily, it is the result of a fairly deep mistake in how the history feature of Artemis works. I should think about the solution for a while before trying to fix it. I'll keep you posted. Happily, this mistake has no impact on fit quality, just on the reporting of prior fits in the history window. B -- Bruce Ravel bra...@bnl.gov National Institute of Standards and Technology Synchrotron Science Group at NSLS-II Building 535A Upton NY, 11973 Homepage:http://bruceravel.github.io/home/ Software:https://github.com/bruceravel Demeter: http://bruceravel.github.io/demeter/ ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
Re: [Ifeffit] Fwd: scattering amplitude by FEFF and Artemis
Dear Feng, On 6/28/07, Feng Wang <[EMAIL PROTECTED]> wrote: > Thank you, Dr. Ravel, > > Could you please just simply tell me the expression for the magnitude of chi > (q) (labelled as |chi(q)|)? Thank you. I'm sure you didn't mean to sound so demanding, but perhaps you would consider following Bruce's suggestion of sending a project file. For what it's worth (in case you missed it while you were reading the docs and tutorials), |chi(q)| = magnitude of the complex chi(q) = FT^(-1) [ chi(R) * Window(R) ] where Window(R) is a Windowing function and chi(R) = FT[ chi(k) * k^w * Window(k) ] where Window(k) is a Windowing function and w is the k-weighting. Both FT's are band-limited (Rmin,Rmax, and kmin,kmax, respectively). The convention used in Ifeffit is that chi(k) is strictly real. This isn't particularly important if you're only interested in the magnitude. I thought your original question was about scattering amplitudes Are these questions related? I couldn't tell much from the plot you sent, as I didn't understand what "X Axis Title" or "Y Axis Title" were meant to represent.Of course, the "scattering amplitude" f(k) is not the only factor setting the amplitude of chi(k). Hope that helps. If not, please let us know what the issue is, --Matt ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
[Ifeffit] S02 and k_min
Hello everyone, I am currently performing a simple curve fit on bulk MoS2 using an atoms file for crystalline MoS2. I've found that increasing k_min on my fit (e.g. from 2 to 4) improves the quality of the fit (R-factor from 0.028 to 0.009), but also increases S02. If I use a large enough k_min (but not so large I run out of data), S02 gets as high as 1.2 +/- 0.05. This trend is observable for single and multiple k-weight fittings. While I understand that S02>1.0 does not necessarily invalidate the fit, I am not sure how to justify which parameter values are the best seeing that "0.8http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
[Ifeffit] Problems with EXAFS Fitting of Metalloprotein Zinc Samples
Hi, I have a general question rather than specific. I have only ever fit XAS data on metalloproteins and one feature that I see is that when fitting Zinc samples in R-space there is no local minima. For Cobalt and Nickel samples I typically get one or a few fits that are obviously significantly better in R-factor (with reasonable distances, sigma^2, etc) but for Zinc this is not the case. I can get many good fits and Zinc likes to increase the coordination up to 8 for all data sets I have ever fit, although there is obviously no physical basis in this. This is true of not just my own proteins but Zinc samples made by collaborators, and after looking through previous group members fit tables, they had similar issues. My understanding is that one of the benefits of fitting in R-space is that there is a local minima, whereas in k-space there are many minima. I was wondering if there was a physical basis for this feature in Zinc samples, or if perhaps my group is not aware of some experimental setup that we should be doing for Zinc that would resolve this problem. Thank you for any help regarding this matter, Carolyn Carr ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit Unsubscribe: http://millenia.cars.aps.anl.gov/mailman/options/ifeffit
Re: [Ifeffit] problem of overestimated E0 (Edge-energy)
Jeong-Eun (I hope that is right), Looking at the feff.inp file, the SCF line has been commented out. This indicates that the self-consistent calculations have not been done. Try: SCF 5 You can adjust the n_scf and ca later if this doesn't converge. This could shift Eo by several eV. Jeremy From: ifeffit-boun...@millenia.cars.aps.anl.gov [mailto:ifeffit-boun...@millenia.cars.aps.anl.gov] On Behalf Of JeongEunSuk Sent: Thursday, January 12, 2012 11:43 PM To: ifeffit Subject: Re: [Ifeffit] problem of overestimated E0 (Edge-energy) Thank Jeremy the feff.inp file and Fourier transformed EXAFS is attached. I fitted the nearest neighbor scattering path, only single scattering Pt and I am sorry, I wrote wrong fitting range Fitting range K-sapce: 3.0 ~ 15 A-1 R -space: 1.3~3.3 A Date: Thu, 12 Jan 2012 16:05:25 -0600 From: kr...@anl.gov To: ifeffit@millenia.cars.aps.anl.gov Subject: Re: [Ifeffit] problem of overestimated E0 (Edge-energy) I think we'll need more information to help out: at a minimum, the feff.inp file. Also, are you fitting just the nearest neighbor scattering path? To begin to answer your question, while it is often the case that Eo falls below the white line peak, this is not categorically true. A relevant example might be PtO2. Jeremy Chemical Sciences and Engineering Division Argonne National Laboratory Argonne, IL 60439 Ph: 630.252.9398 Fx: 630.252.9917 Email: kr...@anl.gov From: ifeffit-boun...@millenia.cars.aps.anl.gov [mailto:ifeffit-boun...@millenia.cars.aps.anl.gov] On Behalf Of JeongEunSuk Sent: Thursday, January 12, 2012 3:47 PM To: ifeffit Subject: [Ifeffit] problem of overestimated E0 (Edge-energy) Hello all I want to understand EO(edge-energy), precisely. (In Artemis, EO is writed as Enor) Generally, EO is energy when electrons start to go out from core atom in XAFS. As you know, the experiments show that to find EO is not easy in XAFS. To remove background, sometimes I chose EO, the value of the maximum derivative in Athena. and when fitting, the E0 is correted by theoritical FEFF. This is my question. The attached file is the figure of Pt foil(Pt L3 edge measurement). I think edge-enegy has to be in range between A and C because electrons start to move to continum state in that range. However, fitted E0 is shifted to C (about 11573eV). and then when removing background I chose E0=11563eV(This is Pt L3 edge). Fitted E0 is overestimated value, compared with whit line(B). That means the calculated EO obtained from FEFF8.0 (using auto-sel! f consistency field potential) is larg! er than that of experiment. Do I need to change SCF potential in FEFF8.0? This is fitting parameters and results(in my case, I used Linux version) To remove background k -range = 2.5 ~ 15, EO=11563eV, Rbkg=1.3, kweight =1 To fit data k -range = 3.0~13.5, R -range =2.3~13.5 1. fitting parameters set macc = 0.0 set so2 = 0.89// reduction factor guess ePt = 0.0 // energy shift set npt1=1.0// the number of Pt (1.0 means 12&nb! sp; Pt atoms around core Pt) gu! essdpt1 = 0.0042 // effective bonding length guesssigpt1=0.005100 //Debye waller factor 2. fitting results fit results, goodness of fit, and error analysis: independent points in data= 8.152 number of variables in fit= 3 degrees of freedom in fit = 5.152 r-factor of fit = 0.002700 chi-square ! ; =1267.097168 ! ;reduce! d chi-square &nb! sp; = 245.926361 feffit found the following values for the variables: variablebest fit valueuncertainty initial guess ept= 10.7581980.8604944.00 dpt1 =0.0064620.0029300.004200 sigpt1 &nb! sp; = &nbs! p; 0.0051140.98 0.005100 correlation between variables variable #1variable #2 correlation eptdpt1 0.926524 all other correlations are less than0.25000 - Because the correlation between E0 and effective bonding length is big, I checked the fit as set bonding and the rest of parameters is variables, and then the result is no! t changed. That means EO still is big. &! nbsp; ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit ___ Ifeffit mailing list Ifeffit@
Re: [Ifeffit] Co fitting questions
Hi Neil: I took your data and fit it with the Co(OH)2 structure but only the first two paths: Co-O and Co-Co. I used a k-range of 2-10 and dk=3 and the r-range of 1-3.5 with dr=0.2. The fit results are as follows R-factor= 0.024528565 Guess parameters +/- uncertainties (initial guess): amp = 1.0648700 +/- 0.1581370(1.) enot=-1.2653240 +/- 1.2834050(0.) dr_o=-0.0140240 +/- 0.0139460(0.) ss_o= 0.0090020 +/- 0.0025450(0.0030) dr_co =-0.0090720 +/- 0.0119710(0.) ss_co = 0.0078130 +/- 0.0016030(0.0030) The sigma squared values for both paths are not unreasonable. This is a fairly disordered structure becuase each of the oxygens has a hydrogen attached to it and they sort of get in each other's way. If you remove one of the hydrogens by oxidizing it, you get CoOOH which is much more ordered as each hydrogen is now close to 2 oxygens. If I add a second Co-O path, I do see a slight improvementin the Co-Co sigma squared but the second Co-O path has a large negative shift in distance and has a huge sigma squared so it has dubious value. The very large sigma squared of this second Co-O path (0.024) is consistent with the disorder I mentioned above. If this is your standard for a catalyst, then you probably only care deeply about the Co-O near neighbor path. That is pretty much independent of what you do with the Co-Co and other Co-O paths. however, note that this structure hae Co-O6 octahedra which may not be relevant for a catalyst on a surface. Cheers, Carlo On Fri, 2 Sep 2016, Neil M Schweitzer wrote: Thanks Carlo, For this sample specifically, I am only trying to get a reasonable estimate of SO2 for use with my samples, which are supported, Co oxide clusters (catalysts). You are right. If it take out the extra O scattering paths and reduce the R-range, the fit becomes significantly better (both R-factor and Reduced chi-square are reduced). However, now the SO2 is ~1.11. Does this make physical sense? What would be the cause of it being too big? Neil -Original Message- From: Ifeffit [mailto:ifeffit-boun...@millenia.cars.aps.anl.gov] On Behalf Of Carlo Segre Sent: Friday, September 02, 2016 3:42 PM To: XAFS Analysis using Ifeffit Subject: Re: [Ifeffit] Co fitting questions hi Neil: The sigma squared values for your first Co-O path and the Co-Co path are not out of line with those I have seen for Co(OH)2. Personally, I would not include the last Co-O path and cut the fitting range down to 3.5A or so. It is possible that the second Co-O path is also not relevant. The distance shift seems to be very large and simply compensating for the peak at 2.7A. Again, I have seen this in my Co(OH)2 samples as well. The question is what do you need to glean from these data. Carlo On Fri, 2 Sep 2016, Neil M Schweitzer wrote: I have been trying to fit a Co(OH)2 reference sample and think I have a good fit, but I have a couple reservations about it and wanted to run it by some people for an expert opinion. If you are interested, I have included the Athena file, an image of the fit, and the fit log file. Please read on! If not, sorry I spammed you. As you can see, the fit contains four paths. They are all single scattering paths, and the paths with the four largest ranks according to feff. All paths share the same SO2 and deltaE. Each path has its own delR and ss. After some work, I got it to the point that the fit looks pretty (R-factor<0.02), but I have several reservations about it: 1) Generally, the ss values are all higher than I would like. 0.007 even seems high to me for a metal-O bond. Am I right about this? Would this indicate that this may have been a poor choice for reference sample (I should mention it is a powder) and it is not very crystalline? Could it mean there was something we overlooked when we recorded the data? 2) The biggest problem with the fit is the large error on ss_O2 and ss_O3. The largest feature at ~2.75 is obviously Co-Co scattering, but the Co-O paths help to fit the shoulder (or feature at ~3.1 in the Real part) in R-space. If I take them out, then the Co path has a large ss with an equally large error. So here is my question. If I add more paths, the error of ss_O2 and ss_O3 will go down, but then the errors on the new path will consequently be large, so when do I stop adding paths? For the purpose of my samples, I am only interested in the first Co-O path and the Co-Co path. Is this fit good enough you would publish it? Please feel free to critique any other aspect of the fit too. Thanks for your input! Neil -- Carlo U. Segre -- Duchossois Leadership Professor of Physics Interim Chair, Department of Chemistry Director, Center for Synchrotron Radiation Rese
Re: [Ifeffit] Exafs distance resolution
Eric, > Is there a physical limitation determining exafs bond distance resolution? There is a physical limit in determining bond distances from EXAFS. > Very often the equation r = pi / 2 deltak is quoted as a measure for > bond distance resolution. The equation dr=pi/(2 *Delta k) gives the distance resolution: the ability to separately see two distances (here Delta k is the data range in k). This is not the same thing as the precision with which a single bond distance can be determined, which is generally quite a bit better than the "resolution". For Delta k ~= 15Ang^-1 (pretty good data), the resolution from the equation above is about ~= 0.1Ang. That is, one could expect to reliably detect a splitting of distances by ~0.1Ang. The precision in R from EXAFS experiments is typically 0.01Ang. This is typically determined by a combination of noise in the data and the accuracy of the phase shift calculations (say, from FEFF). For certain cases, it's entirely feasible to detect *changes* in bond distances with even better precision. One paper not so long ago (Pettifer, et al, Nature 435 pp78, 2005) claimed a precision of 10fm. > But as i understand this equation is related > to the fourier transform traditionally used for exafs analysis. > If exafs fitting is done in k-space, on the raw exafs data without > applying fourier or any other filtering transformation is there a > physical limitation determining exafs bond distance resolution? Whether or not Fourier transforms are used in the analysis is "mostly" immaterial. That is, EXAFS is an interference technique, and we measure in k (or E) space to make statements about R space, so the limits are fundamental, not an artifact of the analysis tools. I say mostly because practical use of Fourier transforms (Fast Fourier Transforms with finite grids and extents) will impose additional restrictions on resolution and precision -- but these are typically finer than 0.1Ang for resolution and 0.01Ang for precision, and so are hardly ever a concern. As an example, FFTs in Ifeffit+Friends use a k-space grid of 0.05Ang^-1 and kmax of 102.4Ang^-1, and a grid in R-space of ~0.03Ang. This would limit resolution to about ~-0.03Ang, which might be a limiting factor if you have data to k~=50Ang^-1. It probably limits precision too, though I do not know to what extent. > This question comes down to the following practical problem. If one has a > theoretical model developed using computational chemistry that predicts > two different bond lengths within one shell, e.g. an octahedral metal > center surrounded by 6 oxygen atoms and this shell is predicted to be > split in three subshells for wich the bond length differs only 0.05 > angstroms; and this model can be fit very well in k-space with the > splitted shell, off course keeping the number of fit parameters below > the nyquist criterion. Is there in such a case any physical reason not > to fit the experimental data with the splitted shell , but with an > averaged 6-atom shell with a larger Debye Waller factor? My guess would be that the EXAFS could probably be fitted just as well with one distance and a slightly larger sigma2 as with 3 separate distances. But this would depend some on the data quality and it might be right at the resolution limits, so I'd recommend trying both models. Cheers, --Matt ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
Re: [Ifeffit] Questions about Athena and XANES
Hi Jenny, > 1. For linear combination fitting, there are three indicators for the > goodness of fitting: R-factor, chi-square and reduced chi-square. Could > anyone tell me how they work? This is actually documented in Athena, and the Users Guide. They are also defined in the Feffit documentation. In short, they are all scaled measures ofSum [(data-fit)^2] R-factor scales this my the data values, and chi-square scales by an estimate of the noise in the data. Reduced chi-square relates to chi-square through the usual statistical definition, in that it is chi-square / (number of free variables in the fit). Of course, chi-square requires one to know the uncertainty in the data -- generally we don't have a great estimate of this. I mean no offense of this, but if you're asking about these then you almost certainly haven't put in an estimate of the uncertainty. So chi-square is probably scaled incorrectly. On top of that, reduced chi-square needs to know the number of independent measurements. Normally one assumes each datum to be independent. This is arguable, but it we can make that assumption for now. But if chi-square is scaled poorly, so is reduced chi-square. If that's too vague, or I misunderstood the question, please ask again. > 2. Since TEY is sensitive for the surface and FY for the bulk (and > surface?), species detected by TEY should be also detected by FY, right? Yes, but TEY samples a much smaller volume of material than FY, so the signal from the volume seen by TEY (that is, the surface) may be insignificant compared to the signal from the volume seen by FY. > 3. How to calculate the maximum analysis depths for TEY and FY? Google/Wikipedia might help here. The sampling depth for TEY is typically dominated by the mean-free-path for the Auger electrons, which is in the range of 20 - 50 Angstroms.Sampling depths for FY are typically set by the absorption length of fluorescence x-rays, which is in the range of 2 to 50 microns (yes, a much more variable range, depending on sample composition). In both cases, you'd need to calculate the depth that the x-ray beam penetrates the sample (depends strongly on matrix) too. In my experience, it's unusual for this to dominate the sampling depth, but it can be significant for FY in high-Z matrices. --Matt ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
Re: [Ifeffit] Co fitting questions
Thanks Carlo, For this sample specifically, I am only trying to get a reasonable estimate of SO2 for use with my samples, which are supported, Co oxide clusters (catalysts). You are right. If it take out the extra O scattering paths and reduce the R-range, the fit becomes significantly better (both R-factor and Reduced chi-square are reduced). However, now the SO2 is ~1.11. Does this make physical sense? What would be the cause of it being too big? Neil -Original Message- From: Ifeffit [mailto:ifeffit-boun...@millenia.cars.aps.anl.gov] On Behalf Of Carlo Segre Sent: Friday, September 02, 2016 3:42 PM To: XAFS Analysis using Ifeffit Subject: Re: [Ifeffit] Co fitting questions hi Neil: The sigma squared values for your first Co-O path and the Co-Co path are not out of line with those I have seen for Co(OH)2. Personally, I would not include the last Co-O path and cut the fitting range down to 3.5A or so. It is possible that the second Co-O path is also not relevant. The distance shift seems to be very large and simply compensating for the peak at 2.7A. Again, I have seen this in my Co(OH)2 samples as well. The question is what do you need to glean from these data. Carlo On Fri, 2 Sep 2016, Neil M Schweitzer wrote: > I have been trying to fit a Co(OH)2 reference sample and think I have a good > fit, but I have a couple reservations about it and wanted to run it by some > people for an expert opinion. If you are interested, I have included the > Athena file, an image of the fit, and the fit log file. Please read on! If > not, sorry I spammed you. > > > > As you can see, the fit contains four paths. They are all single scattering > paths, and the paths with the four largest ranks according to feff. All paths > share the same SO2 and deltaE. Each path has its own delR and ss. After some > work, I got it to the point that the fit looks pretty (R-factor<0.02), but I > have several reservations about it: > > 1) Generally, the ss values are all higher than I would like. 0.007 even > seems high to me for a metal-O bond. Am I right about this? Would this > indicate that this may have been a poor choice for reference sample (I should > mention it is a powder) and it is not very crystalline? Could it mean there > was something we overlooked when we recorded the data? > > 2) The biggest problem with the fit is the large error on ss_O2 and > ss_O3. The largest feature at ~2.75 is obviously Co-Co scattering, but the > Co-O paths help to fit the shoulder (or feature at ~3.1 in the Real part) in > R-space. If I take them out, then the Co path has a large ss with an equally > large error. So here is my question. If I add more paths, the error of ss_O2 > and ss_O3 will go down, but then the errors on the new path will consequently > be large, so when do I stop adding paths? For the purpose of my samples, I am > only interested in the first Co-O path and the Co-Co path. > > Is this fit good enough you would publish it? Please feel free to critique > any other aspect of the fit too. > > Thanks for your input! > > Neil > -- Carlo U. Segre -- Duchossois Leadership Professor of Physics Interim Chair, Department of Chemistry Director, Center for Synchrotron Radiation Research and Instrumentation Illinois Institute of Technology Voice: 312.567.3498Fax: 312.567.3494 se...@iit.edu https://urldefense.proofpoint.com/v2/url?u=http-3A__phys.iit.edu_-7Esegre&d=CwICAg&c=yHlS04HhBraes5BQ9ueu5zKhE7rtNXt_d012z2PA6ws&r=oD5QfHEvBMM5YYrnfMF2YrJNX5aSKvlIRGd2B3iC9kQ&m=UHovCVboippuwjHS83MUbFyIwD3zbmNtLtJdSaRupGY&s=vR2qFm6nzIZ4Hvsa87KtvYjUzdKhqohA72GQpeTS-wg&e= se...@debian.org ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov https://urldefense.proofpoint.com/v2/url?u=http-3A__millenia.cars.aps.anl.gov_mailman_listinfo_ifeffit&d=CwICAg&c=yHlS04HhBraes5BQ9ueu5zKhE7rtNXt_d012z2PA6ws&r=oD5QfHEvBMM5YYrnfMF2YrJNX5aSKvlIRGd2B3iC9kQ&m=UHovCVboippuwjHS83MUbFyIwD3zbmNtLtJdSaRupGY&s=0zz-kQkc5YsoGwUAbnlBmAh-FL0edswrqe2m8WHLMY4&e= Unsubscribe: https://urldefense.proofpoint.com/v2/url?u=http-3A__millenia.cars.aps.anl.gov_mailman_options_ifeffit&d=CwICAg&c=yHlS04HhBraes5BQ9ueu5zKhE7rtNXt_d012z2PA6ws&r=oD5QfHEvBMM5YYrnfMF2YrJNX5aSKvlIRGd2B3iC9kQ&m=UHovCVboippuwjHS83MUbFyIwD3zbmNtLtJdSaRupGY&s=O7NfUTdRgH9IJMhcNbrkMTJBBXYNzXtNppPwcG2TkYc&e= ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit Unsubscribe: http://millenia.cars.aps.anl.gov/mailman/options/ifeffit
Re: [Ifeffit] Data being overwritten in Artemis history window
On 03/09/2015 04:17 AM, Godfrey, Ian wrote: In the history window some, but not all, data from previous fits seems to get overwritten when running a new fit. Specifically I've noticed this happening with the information in the "Data set" section. To reproduce run a QFS fit with some R-space fitting windows (say 2-4); at this point the log will be displayed correctly in the history window. Now change the R window (say 1.5-3.5) and run the fit again. When you go to the history window the R window information will be displayed correctly for the most recent fit but, for the previous fit it will have been overwritten by the newer fit. Some of the other info, such as R-factor by k-weight seems to get overwritten too. A video of this behaviour can be found here: https://wwwa-e.ucl.ac.uk/cgi-bin/dropbox/dropbox.cgi?state=pickup_info&id=29d3e5c2 password: 54c8545f System info: Win 8.1 Enterprise x64 running Demeter 0.9.22 pre release x64; log attached. Ian, First off, I really like your way of making a bug report. Your video makes the problem completely clear. (I also rather like your background image.) While all my worst days begin with email that starts "Sorry ... another bug report!", an unambiguous explanation makes me very happy. As for the problem you are reporting -- yikes! That's really troubling. I'll look into it. Cheers, B -- Bruce Ravel bra...@bnl.gov National Institute of Standards and Technology Synchrotron Science Group at NSLS-II Building 535A Upton NY, 11973 Homepage:http://bruceravel.github.io/home/ Software:https://github.com/bruceravel Demeter: http://bruceravel.github.io/demeter/ ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
Re: [Ifeffit] Asymmetric error bars in IFeffit
Scott, It is a strange result. Suppose you fit a bulk metal foil and vary the 1nn coordination number. You will not get 12 +/- 1000. You will get about 12 +/- 0.3 depending on the data quality and the k range, and on the amplitude factor you fix constant. Then, suppose you take your formula for a particle radius from your JAP article and propagate this uncertainty to get the radius uncertainty. That would give you a huge error because you are in the flat region of the N(R) function and R does bit affect N. The meaning of your large error bar is, I think, that you are in such a large limit of sizes that they cannot be inverted to get N and thus the errors cannot be propagated to find Delta R. Why don't you try to obtain N instead of R? You will get much smaller error bars and you can find the lower R limit from your N(R) equation (by plugging in N - deltaN you will find R - delta R). The right limit is infinity as you pointed out. Anatoly From: ifeffit-boun...@millenia.cars.aps.anl.gov To: XAFS Analysis using Ifeffit Sent: Fri Oct 22 16:23:08 2010 Subject: [Ifeffit] Asymmetric error bars in IFeffit Hi all, I'm puzzling over an issue with my latest analysis, and it seemed like the sort of thing where this mailing list might have some good ideas. First, a little background on the analysis. It is a simultaneous fit to four samples, made of various combinations of three phases. Mossbauer has established which samples include which phases. One of the phases itself has two crystallographically inequivalent absorbing sites. The result is that the fit includes 12 Feff calculations, four data sets, and 1000 paths. Remarkably, everything works quite well, yielding a satisfying and informative fit. Depending on the details, the fit takes about 90 minutes to run. Kudos to Ifeffit and Horae for making such a thing possible! Several of the parameters that the fit finds are "characteristic crystallite radii" for the individual phases. In my published fits, I often include a factor that accounts for the fact that a phase is nanoscale in a crude way: it assumes the phase is present as spheres of uniform radius and applies a suppression factor to the coordination numbers of the paths as a function of that radius and of the absorber-scatterer distance. Even though this model is rarely strictly correct in terms of morphology and size dispersion, it gives a first-order approximation to the effect of the reduced coordination numbers found in nanoscale materials. Some people, notably Anatoly Frenkel, have published models which deal with this effect much more realistically. But those techniques also require more fitted variables and work best with fairly well-behaved samples. I tend to work with "messy" chemical samples of free nanoparticles where the assumption of sphericity isn't terrible, and the size dispersion is difficult to model accurately. At any rate, the project I'm currently working on includes a fitted characteristic radius of the type I've described for each of the phases in each of the samples. And again, it seems to work pretty well, yielding values that are plausible and largely stable. That's the background information. Now for my question: The effect of the characteristic radius on the spectrum is a strongly nonlinear function of that radius. For example, the difference between the EXAFS spectra of 100 nm and 1000 nm single crystals due to the coordination number effect is completely negligible. The difference between 1 nm and 10 nm crystals, however, is huge. So for very small crystallites, IFeffit reports perfectly reasonable error bars: the radius is 0.7 +/- 0.3 nm, for instance. For somewhat larger crystallites, however, it tends to report values like 10 +/- 500 nm. I understand why it does that: it's evaluating how much the parameter would have to change by to have a given impact on the chi square of the fit. And it turns out that once you get to about 10 nm, the size could go arbitrarily higher than that and not change the spectrum much at all. But it couldn't go that much lower without affecting the spectrum. So what IFeffit means is something like "the best fit value is 10 nm, and it is probable that the value is at least 4 nm." But it's operating under the assumption that the dependence of chi-square on the parameter is parabolic, so it comes up with a compromise between a 6 nm error bar on the low side and an infinitely large error bar on the high side. Compromising with infinity, however, rarely yields sensible results. Thus my question is if anyone can think of a way to extract some sense of these asymmetric error bars from IFeffit. Here are possibilities I've considered: --Fit something like the log of the characteristic radius, rather than the radius itself. That creates an asymmetric error bar for the r
Re: [Ifeffit] R quality factor in k space
On Fri, Apr 17, 2009 at 8:08 AM, Cammelli Sebastiano wrote: > > In the case of a linear combination fitting on the k space performed by > ATHENA, the <∆chi> needs a correction. Is it correct to write: > > R_factor ≡ < ∆chi(k space))> = √[ ∑ (chi_C(ki) – chi_E(ki))2 / ∑( > chi_E(ki))2] ? > > Where Chi_C(ki) = x1*chi1(k)+x2*chi2(k) : chi1 and chi2 are the EXAFS > functions of the two reference samples used for the linear combination > procedure and x1, x2 (with 0 is the EXAFS experimental function of the investigated sample. > Yes, I that is correct. For fits in k-space, the chi data is often k-weighted, in which case all the 'chi' functions in these formulae should be the k-weighted chi(k). --Matt ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
Re: [Ifeffit] Questions on Correlated Debye in FEFF6
Doran, You mentioned not finding what you were looking for in the code, so most of my answers are in the form of links to the relevant bits of code. I have just recently begun learning about EXAFS and running EXAFS simulations using FEFF6. I have a few very basic questions about the underlying calculations for the correlated Debye model implemented in FEFF6 (called by "DEBYE" keyword). For the questions below, I am assuming I input a single crystallographic structure and want the correlated Debye model to simulate the influence of a thermal distribution on the EXAFS spectrum. I would appreciate any insight you can give me into the questions below. I would also welcome any and all references for the original papers where that is appropriate. This is the reference for the correlated Debye model used in Feff, Ifeffit, and Larch: http://dx.doi.org/10.1103/PhysRevB.20.4908 1. Are the Debye-Waller factors calculated for each path individually? (It seems like they should be since the paths will have different levels of influence from the thermal distribution of atomic positions) Yes. From the Ifeffit manual: http://cars.uchicago.edu/~ifeffit/refman/node19.html From the Larch manual: http://cars.uchicago.edu/xraylarch/xafs/feffpaths.html#models-for-calculating 2. Assuming the DW factors are calculated path-by-path, is the magnitude of the DW factor determined by assuming the total path length R is the appropriate length to use for the correlation term in the Debye spectral density? It seems like it would not be reasonable to treat all paths of the same R as having the same Debye-Waller factor since a single scattering path and multiple scattering paths are perturbed by a different set of relative atomic motion that are likely to have different correlations. I couldn’t locate a clear statement about how this calculations is actually done within the code. In Ifeffit: https://github.com/newville/ifeffit/blob/master/src/lib/sigms.f In Larch: https://github.com/xraypy/xraylarch/blob/master/plugins/xafs/sigma2_models.py The CDM is calculated on a path-by-path basis. R matters. 3. Is the C1 shift that results from the vibrational motion normal to the bond axis along a path incorporated in the calculation? (Presumably using \Delta C1 = sigma_perp^2/(2)) And is this formula still appropriate in multiple-scattering paths? In Ifeffit: https://github.com/newville/ifeffit/blob/master/src/lib/chipth.f#L103 In Larch: https://github.com/xraypy/xraylarch/blob/master/plugins/xafs/feffdat.py#L377 4. Assuming the C1 shift is incorporated, does the correlated Debye model assume that the perpendicular and parallel displacements have the same spectral density? I think the answer is yes, but I am not sure I understand the question. HTH, B -- Bruce Ravel bra...@bnl.gov National Institute of Standards and Technology Synchrotron Science Group at NSLS-II Building 535A Upton NY, 11973 Homepage:http://bruceravel.github.io/home/ Software:https://github.com/bruceravel Demeter: http://bruceravel.github.io/demeter/ ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
[Ifeffit] About export Chi(K) file
Dear, I want to ask why the exported Chi(K) file from Artermis can not repeat the figure like in Graphic window #1 - [Athena]. I planed to output the fitted data from Artemis and plot in Origin 8.0 or Excel ect, but the figure based on the output data seems strange for Chi(K) file. For Chi(R), it was ok, the shape plotted in Origin 8.0 was the same like in Graphic window #1 - [Athena]. I do not know why?In addition, I want to ask a question about Artermis fitting. I used 5 paths for fitting, and it seemed a good fitting from the figure in Graphic window #1 - [Athena]. But the results showed that only path 1 had good values of N, R-factor, Chi-square, amp and sigma^2. If I choose only path 1 for fitting, the figure in Graphic window #1 - [Athena] showed only the highest peak fitted perfectly. Thus, I am not sure how many path that I should choose for fitting(I know only path 1 is available). The problem is, how can I export the fitted results, with or without ohter paths? Tha! nks!Best wishesMingliang___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
Re: [Ifeffit] Negative ss problem
Hello, It seems to me that you have some more problems than just ss values. The data collection range seems a little short just ~300 eV past the edge. Amp is quite high and delr is very large. I am an expert by no means but I might suggest that you have the wrong model. The model is trying to compensate for high R space magnitude by making amp above 1 and ss negative. Have you considered your data processing in Athena? Did you use the default settings? I would guess Cu-O bonds might be too short for the presets in Athena. How did you check your model? Buena salud, Chris Patridge On Jul 14, 2010, at 2:59 AM, Abhijeet Gaur wrote: Hi all, I read the discussion on negative Debye waller factor. As per the discussion the negative value of this factor shows that the model has shortcomings, so it should be corrected. I am also getting the same problem while fitting one of my samples. It is a Cu complex whose EXAFS data is taken at Dispersive EXAFS beamline at RRCAT, Indore, India. In the complex the nearest neighbours of Copper atom are Nitrogen and Oxygen. I am getting a very good fit upto 3rd shell but the problem is that all ss parameters are coming negative. I checked the model it seem correct. Also I am getting a peak below 1 Angs which is also getting fitted but I am not able to get that whether it is a real or due to some noise. I am attaching herewith the results of data analysis and fitting. Thanks in advance With regards Abhijeet Gaur Vikram University Ujjain, INDIA ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
Re: [Ifeffit] Sixpack, PCA controll, "IND" column
Amazon has lots of used copies. I like original sources -- especially since you can look at them and see, for example, that a particular function is described under the heading, "Empirical Methods" instead of relying on what someone told you on the Internet. Sam's Sixpack paper cites Malinowski's 1977 paper, and both are available online. S M Webb (2005) SIXpack: a graphical user interface for XAS analysis using IFEFFIT. Phys. Scr. T115, 1011. E R Malinowski (1977) Determination of the Number of Factors and the Experimental Error in a Data Matrix. Anal Chem 49, 612. -Leslie -Original Message- From: ifeffit-boun...@millenia.cars.aps.anl.gov [mailto:ifeffit-boun...@millenia.cars.aps.anl.gov] On Behalf Of Matthew Marcus Sent: Thursday, June 21, 2012 9:29 AM To: XAFS Analysis using Ifeffit Subject: Re: [Ifeffit] Sixpack, PCA controll, "IND" column That book is out of print and hard to get. You should refer to later papers. The IND function is not necessarily robust. It's not rigorously derived, but is sort of empirical. mam On 6/21/2012 9:20 AM, Baker, Leslie wrote: > This is the factor indicator function. Its minimum can be used to > indicate the correct number of meaningful factors. > > There's an explanation here: > http://www.vub.ac.be/fabi/multi/pcr/chaps/chap6.html > > For more information, see Malinowski's book Factor Analysis in > Chemistry. > > -Leslie > > > -Original Message- > > Hello, > > does anyone know the meaning of the IND column in the PCA controll > field of sixpack (version 0.63)? > > I did not found a hint in the sixpack documentation. > > Best regards > Joerg > > > > ** > Leslie L. Baker, Ph.D. > Department of Plant, Soil and Entomological Sciences University of > Idaho Moscow, ID 83844-2339 > 208-885-9239 > http://scholar.google.com/citations?user=ejpH5p0J > > ___ > Ifeffit mailing list > Ifeffit@millenia.cars.aps.anl.gov > http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit > ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
Re: [Ifeffit] Writing a paper
On Monday, May 07, 2012 04:10:35 PM mattie.p...@huskers.unl.edu wrote: > Hello Everyone, > > I am in the process of fitting XAFS data for a paper and I was wondering > what type of information should should be included. I remember coming > across a website that had this information on it awhile ago but I can't > seem to find my way back. We would like to publish a qualitative XANES > paper and an EXAFS paper. Any suggestions on the type of information > (plots, tables, R-factor, etc.) that should be included in each paper > separately would be appreciated. Was this the page you were looking for? http://xafs.org/Reporting_EXAFS_Analysis Incomplete, but useful. B -- Bruce Ravel bra...@bnl.gov National Institute of Standards and Technology Synchrotron Methods Group at NSLS --- Beamlines U7A, X24A, X23A2 Building 535A Upton NY, 11973 Homepage:http://xafs.org/BruceRavel Software:https://github.com/bruceravel ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
Re: [Ifeffit] Cadmium K-edge
Hi Alan, Looking at the real part of FT, I am convinced that O atom will justify for peaks at 1.8 and 2.3 A in sample 1. One of the possibilities for sample 2 to be different is, it has higher ss2 for Cd-O (as can be seen from lower amplitude of first peak). If Cd loading in sample 1 is lower than sample 2, then it makes sense to me that Cd is bound to higher affinity (and less disordered) sites on Sodium Titanate nanotube in the sample1. As the Cd loading increases, Cd starts going to lower affinity albeit more disordered sites, making Cd-O bonding more disordered than sample 1. Other possibilities include coexistence of O and Na in the first shell of sample 2, which might be interfering destructively and dampening the peak at 2.3 A). Have you tried that scenario? It might not be trivial to distinguish O bonding with high ss2 from O and Na in the first shell. But you can try that out by splitting the first shell at two different distances with smaller ss2 values. It is not obvious to me that your data supports 2nd shell Cd-Ti interaction. In the fit you described, your E_not2 and ss_2 are very high. The amp_2 is highly correlated with ss_2, and amp_2 value is close to its error bar. Put together, these two parameters makes me suspicious of your 2nd shell fit. Your Chi data does not necessarily show clear Cd-Ti interaction either. In my opinion Cd-Ti interaction would result in high amplitude of oscillation in chi (and correspondingly strong peak in FT). However, things can behave differently in case of nanomaterials and you might have some contribution of Ti in your spectra. If this is a significant part of your manuscript, you will have to convince the reviewers. Good Luck, Bhoopesh On Sun, Jan 9, 2011 at 11:43 PM, Alan Du wrote: > Hi Bhoopesh and Scott, > > I should have given a description of my project. Yes Scott, the work is to > investigate the binding mechanisms of aqueous cadmium onto sodium titanate > nanotubes. Spectrum of Sample 1 and 2 obtained from merging 9 scans and 4 > scans, respectively. > > A quick check in Athena and, indeed, the white line of Samples are higher > than CdO. I'm not sure the reason behind it though. It is likely that > cadmium binds to the surface of substrate rather than inside the bulk. The > lack of distinct peaks after 1.8 Å means that there are not many scatters > around the absorber? > > Bhoopesh, as requested, I have attached the real part of FT ( > http://img585.imageshack.us/i/ftreal.jpg/). I haven't got a chance to > interpret them. > > From preliminary fitting of Sample 1, the major and minor peaks at 1.8 and > 2.3 Å could be described by a Cd-O path (CdO). This interests me because > Sample 2 does not have a peak at 2.3 Å, meaning there is another single > scattering path for Sample 2?. > > The peaks at 3 Å were fitted with Cd-Ti path (CdTiO3). No multiple > scattering paths used. The best fit goes something like this: > > > > Independent points = 13.166992187 > Number of variables = 8.0 > Chi-square =1534.709946959 > Reduced Chi-square = 297.021921317 > R-factor = 0.000128095 > Measurement uncertainty (k) = 0.60423 > Measurement uncertainty (R) = 0.004455442 > Number of data sets = 1.0 > > Guess parameters +/- uncertainties (initial guess): > amp = 0.9242390 +/- 0.0509920(1.) > enot= 1.3950420 +/- 0.5425380(0.) > delr=-0.0872060 +/- 0.0051060(0.) > ss = 0.0113250 +/- 0.0008480(0.0030) > amp_2 = 0.2441320 +/- 0.1905250(1.) > enot_2 =22.5261260 +/- 4.5990590(0.) > delr_2 = 0.2510860 +/- 0.0719080(0.) > ss_2= 0.0274690 +/- 0.0128040(0.0030) > > Correlations between variables: >amp_2 and ss_2 --> 0.9342 > enot_2 and delr_2 --> 0.9133 > amp and ss --> 0.8865 > enot and delr --> 0.8632 >amp_2 and delr_2 --> 0.3040 > delr_2 and ss_2 --> 0.2888 > All other correlations are below 0.25 > > k-range = 2.000 - 9.000 > dk = 1.000 > k-window= hanning > k-weight= 3 > R-range = 1.000 - 4.000 > dR = 0.000 > R-window= hanning > fitting space = R > background function = none > phase correction= none > > > R-factor for this data set = 0.00270 > > >
Re: [Ifeffit] Estimation of S02
Hi Hiroshi, questions very similar to yours have already been asked in the mailing list and I still think the best answers are those available at: 1- Sections 4,8, 11-13 at http://cars9.uchicago.edu/iffwiki/FAQ/FeffitModeling 2- This previous thread from the mailing list: http://www.mail-archive.com/ifeffit@millenia.cars.aps.anl.gov/msg00182.html 3- This one as well: http://www.mail-archive.com/ifeffit@millenia.cars.aps.anl.gov/msg00368.html As Bruce, Matt, Scott and many others have said, there is no "one fits all" solution, so I suggest you start from the considerations found in the links above to select the best approach to your specific system. And take a good look at other previous threads in the mailing list - seek and thou shall find... As far as correlations are concerned, "That is the nature of the exafs fitting problem. A correlation of 0.8 for either of those pairs (amp/MSRD and E0/dr) is quite common." (quoting http://www.mail-archive.com/ifeffit@millenia.cars.aps.anl.gov/msg00523.html). Excellent pieces of advice on how to handle this problem can be found in the links mentioned above and the best I can do is direct you to them. Sorry if this is not the straight answer you were hoping for. Regarding your Athena project, I suggest tweaking the position of E0 and the k and R windows according to the advice provided in the links above. The experimental data looks nice and clean up to k~14.5 A-1. Best of luck, Leandro 2008/10/9 Hiroshi Oji <[EMAIL PROTECTED]>: > Hi Matthias and Leandro, > > Thank you very much for your reply. > > I checked the DW-factor (MSRD) and found it also varies significantly > depending on Fit k-weight as follows. > > kw amp ss > 1 0.8145660 +/- 0.0486470 0.0073230 +/- 0.0005240 > 2 0.9230700 +/- 0.0673820 0.0082070 +/- 0.0005070 > 3 1.0439100 +/- 0.0854950 0.0089560 +/- 0.0005100 > 1,2,3 0.9081570 +/- 0.0722180 0.0081660 +/- 0.0005920 > > The correation between these variables reported by Artemis are very > strong, especially for kw=3. > > kw corration between amp and ss > 10.8469 > 20.8992 > 30.9543 > 1,2,30.8543 > > So, it seems to me that the amps obtaied by kw=1 and 1,2,3 with less > degree are more reliable. > > If the DW-factor is fixed, for example, to ss = 0.008, the variation of > amp become small as follows, > > kw amp ss > 1 0.8674610 +/- 0.0296350 0.008 (fixed) > 2 0.8984650 +/- 0.0260200 0.008 (fixed) > 3 0.8998030 +/- 0.0327720 0.008 (fixed) > 1,2,3 0.8898850 +/- 0.0325530 0.008 (fixed) > > But I don't know how to determine the appropriate DW-factor. Could you > give me advice or comment on this problem? > > By the way, I attached the Athena project file of Zr-foil which I > analyzed. I am glad if you kindly check it. > > Thank you for your coopration in advance, > Best regards, > > Hiroshi > > Matthias Bauer wrote: >> hi hiroshi, >> i did not have a look at the attached project, but what paramteres did >> you vary? even if you use different k-weightings, there is still the >> strong correlation of N,S02 and the Debye-Waller like factor. so as long >> as you do not keep two of these three on a certain value, your S02 might >> vary to some extend, which will be more significant for shells beyond >> the first one. anyway, it would be a great thing to hear some comment on >> a S02 value higher than one, which is by definition of S02 not possible. >> in most analyses the electron mean free path is not iterated, which can >> be an explanation of unphysical values of S02, but than it should be >> considered as a "net" factor accounting for both intrinsic and extrinsic >> losses. am i right? >> best regards >> matthias >> >> Leandro Araujo wrote: >>> Hi Hiroshi, >>> >>> your variation in SO2 does sound a bit too big, so I'll try to help >>> adding my 50c and hopefully more people will jump in. >>> It seems to me that your window in k-space is going a bit lower than >>> it should - you seem to be including signal from the xanes region in >>> your fit and that is not a good thing. >>> I did some really quick fits using your project and just changing the >>> window from k ~ 2-14 to k ~ 4.8-14. Then I got the following values: >>> kw amp >>>1 1.0065350+/-0.0788250 >>>2 1.0359800+/-0.0888140 >>>3 1.0749950+/-0.0946640 >>> 1-3 1.0322490+/-0.0866650 >>> That seems a more reasonable variation to me. But maybe I'm being >>> tricked by the fact that you have a split first she
Re: [Ifeffit] Trouble with fitting with Arthemis
Hi Bruce, I send to you the project. 2009/1/13 Bruce Ravel > > Hi Kleper, > > But your reduced chi-square is only 10^35. That seems like a pretty good > fit... ;-) > > There is obviously a numerical problem, corrupted data, corrupted project > file -- something like that. > > Can you send me the project file? > > B > > > Please, help me. When I try to do any fit in Arthemis, setting all > > parameters unless one, been this one any of the parameters, the fit gives > > for the answer -1. +/- 0.00 like example down. What is happening? > > > > > > Independent points = 8.239257812 > > Number of variables = 1.0 > > Chi-square = 0.12000E+37 > > Reduced Chi-square = 0.165762849E+36 > > R-factor= NaN > > Measurement uncertainty (k) = 0.000437667 > > Measurement uncertainty (R) = 0.000724906 > > Number of data sets = 1.0 > > > > Guess parameters +/- uncertainties (initial guess): > > * amp =-1.000 +/- 0.000(1.)* > > Set parameters: > > enot= 0 > > delr= 0 > > ss = 0.003 > > c3 = 0.0001 > > c4 = 0.1 > > > > -- > > Bruce Ravel bra...@bnl.gov > > National Institute of Standards and Technology > Synchrotron Methods Group at NSLS --- Beamlines U7A, X24A, X23A2 > Building 535A > Upton NY, 11973 > > My homepage:http://xafs.org/BruceRavel > EXAFS software: http://cars9.uchicago.edu/~ravel/software/exafs/ > ___ > Ifeffit mailing list > Ifeffit@millenia.cars.aps.anl.gov > http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit > -- Kleper de Oliveira Rocha Doutorando em Engenharia Química Departamento de Engenharia Química/UFSCar Tels. 55 016 3351-8694 PtAl H2 500.prj Description: application/gzip-compressed ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
Re: [Ifeffit] Multiple data set fit limit
Artemis gives me message “ -- falling back to Ifeffit”. I assume it runs Ifeffit which does exactly what Bruce described: 3 data set refined to completion with sensible refined parameter, however, R-factor for 3rd data set is 1. (overall R for 3 data set is huge too) and after-fit plot for 3rd data set is missing, only experimental one shown. I am using latest versions of programs. Victor From: Ifeffit [mailto:ifeffit-boun...@millenia.cars.aps.anl.gov] On Behalf Of Matt Newville Sent: Thursday, 9 March 2017 12:56 PM To: XAFS Analysis using Ifeffit Subject: Re: [Ifeffit] Multiple data set fit limit On Wed, Mar 8, 2017 at 1:58 PM, Bruce Ravel mailto:bra...@bnl.gov>> wrote: On 03/08/2017 10:53 AM, Bruce Ravel wrote: Well . a multiple data set fit using larch runs to completion and reports sensible values for parameters, but does not manage the data sets correctly. One obvious sign that something has gone wrong is the after-fit plot attached. Yikes! This turned out to be a few Larch syntax problems. I just checked a fix into github. As far as I know, the head of github has an Artemis that works for single and multiple data set fits with Larch or Ifeffit. Awesome! --Matt ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit Unsubscribe: http://millenia.cars.aps.anl.gov/mailman/options/ifeffit
Re: [Ifeffit] Questions on Correlated Debye in FEFF6
Hi Doran, Bruce, Sorry for not responding earlier, and thanks Bruce for giving links. I'll make a few comments, which might suggest why I was hesitant to respond earlier. On Thu, Jun 11, 2015 at 2:18 PM, Bennett, Doran (D) wrote: > Hi Everyone, > > > > I have just recently begun learning about EXAFS and running EXAFS > simulations using FEFF6. I have a few very basic questions about the > underlying calculations for the correlated Debye model implemented in FEFF6 > (called by "DEBYE" keyword). For the questions below, I am assuming I input > a single crystallographic structure and want the correlated Debye model to > simulate the influence of a thermal distribution on the EXAFS spectrum. I > would appreciate any insight you can give me into the questions below. I > would also welcome any and all references for the original papers where > that is appropriate. > > > > 1. Are the Debye-Waller factors calculated for each path individually? (It > seems like they should be since the paths will have different levels of > influence from the thermal distribution of atomic positions) > Yes, they are. > > > 2. Assuming the DW factors are calculated path-by-path, is the magnitude > of the DW factor determined by assuming the total path length R is the > appropriate length to use for the correlation term in the Debye spectral > density? It seems like it would not be reasonable to treat all paths of the > same R as having the same Debye-Waller factor since a single scattering > path and multiple scattering paths are perturbed by a different set of > relative atomic motion that are likely to have different correlations. I > couldn’t locate a clear statement about how this calculations is actually > done within the code. > DW Factors are calculated for each path, R does matter, but so does the path geometry. Bruce gave two links to the ifeffit / larch side of the calculation. The sigms.f link is the one that really does the meat of the work. > > 3. Is the C1 shift that results from the vibrational motion normal to the > bond axis along a path incorporated in the calculation? (Presumably using > \Delta C1 = sigma_perp^2/(2)) And is this formula still appropriate in > multiple-scattering paths? > > OK, I apologize in advance for ranting here. The literature is chock full of this sort of nomenclature and discussions. In my view, there is much confusion about this throughout the literature and community. Yeah, I am sort of saying "everyone else is wrong". Single-Scattering XAFS is exactly one-dimensional. It is sensitive to R. There is no perpendicular and no parallel. There is, quite simply, nothing to be perpendicular to.Similarly, sigma is the variance in interatomic distance. There is no directionality at all to this quantity. If you see sigma_perp or sigma_par in a paper or any discussion of XAFS, you can be assured that it is wrong. It would be easy to suggest that this work should be ignored, but there is so much literature with this in it that it cannot be ignored. Many people publishing work understand the subtle distinctions, but the confusion caused is a problem. Vibrations give a distribution of interatomic distances, which is all XAFS is sensitive to. If you're comparing interatomic distances from XAFS to the distances between lattice points, then vibrations will indeed cause a difference in these two distances, with the interatomic distance being larger than the distance between lattice points. This difference will scale as sigma2/r (where sigma is the variance in interatomic distances), under some assumptions about how the motions of the two atoms around their respective lattice points are correlated. This is actually well-described in the literature. This difference between interatomic distance and the distance between lattice points is absolutely NOT accounted for in any part of the XAFS calculation. The XAFS calculation is concerned with interatomic distances, not distance between lattice points. There is a similar term in the XAFS equation that is a correction to getting accurate interatomic distances in the presence of vibrations that also scales as sigma2. This correction accounts for the effect of having a distribution of R in the 1/R^2 term in the XAFS equation. Again, this is to get accurate interatomic distances, not distances between lattice points. To the extent that the formalism applies to multiple scattering, the angular extent of such vibrations is not directly accounted for, only the effect on the half path length R. > 4. Assuming the C1 shift is incorporated, does the correlated Debye > model assume that the perpendicular and parallel displacements have the > same spectral density? > There is no perpendicular to R. Sorry for the rant. --Matt ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
Re: [Ifeffit] Energy shift
Your attachment do not help in this case...
Do you know something more about sample? I suppose it is a thin layer.
Have you checked if you have no defects, vacancies, etc?
I suppose that you can follow instructions given in this post
http://millenia.cars.aps.anl.gov/pipermail/ifeffit/2009-January/008522.html
but you can be also interested in this topic:
http://millenia.cars.aps.anl.gov/pipermail/ifeffit/2009-June/004293.html
and especially in last posts.
you can also try this suggestion
http://millenia.cars.aps.anl.gov/pipermail/ifeffit/2010-June/009471.html
In general - could you precise, what is k_{min} for your fit, and did
you use self consistent potential in calculations?
W dniu 11-10-06 02:28, JeongEunSuk pisze:
Thank Dariuz and Bruce.
TiO is deposited on Si substrate and PtO is fabricated on TiO2.
I measered EXAFS with Pt L3 edge(11563eV) and The model is decided
from FEFF8.0.
PtO has only fist shell like attached files So I chose the simple
model with octahedral structure (probe atom Pt, others O)
When the EXAFS was fitted by feffit, the variables were three eo(Enot
in Artemis, energy shift), do1(distance factor), sigo1(debye-waller
factor).
the results of fit is as following
variablebest fit valueuncertainty initial guess
eo = 19.2833981.7264260.00
do1= -0.0232270.0095570.096000
sigo1 =0.0037900.0005830.003047
r-factor: 11
reduced-chi square: 95
Energy shift by fit shows an amount of difference from Pt L3 edge. It
is my problem.
To reduce the energy shift, I tried to remove background carefully
again and to change distance Pt-O.
However the result was failed.
Date: Wed, 5 Oct 2011 08:24:16 +0200
From: ki...@ifj.edu.pl
To: ifeffit@millenia.cars.aps.anl.gov
Subject: Re: [Ifeffit] Energy shift
Hi,
could say more precise what kind of energy shift you are talking
about? the position of the white line or the Enot in Artemis. How big
it is? Which version of Feff do you use? What do you mean writing
"removing background carefully"? Background in the EXAFS fit? Any
pictures to illustrate problem are welcome
W dniu 11-10-05 03:25, JeongEunSuk pisze:
Hell all
I have the study for PtO nanoparticles with EXAFS.
When I fitted the data to model, I had a problem for energy shift.
I thought that the energy shift obtained from fitting must be
below White line. However it was over white line.
Although I removed background carefully and changed bond length in
model, the energy shift was still big.
I want to know other factors which affect energy shift.
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Re: [Ifeffit] Manuscript comments regarding EXAFS modeling
Hi Peng, This will echo much of what Matthew Marcus wrote: For comment 1 on S02, picking a value of 0.85 seems reasonable. I think the reviewer is asking you to explain how you got that value. Saying something like "we chose that value so that the data from a simple metal foil (or simple metal oxide, etc) gave the expected first shell coordination number" should be enough. Typically, S02 is determined once for a given set of data with the same beamline conditions and *not* varying from sample to sample. For comment 2 on correlation, I would emphasize that N and sigma2 are well-known to be correlated and that this correlation cannot be eliminated. The correlation is "managed" as all correlations are managed - by a statistical analysis of that correlation. The uncertainties reported for all fitting variables always take those correlations into account. That is just a normal part of the analysis. There is a common misconception that using multiple k-weights "eliminates" correlations between variables. It does not. It is available in ifeffit/artemis/larch to try to help find more robust solutions. In my experience, simultaneously using k-weights of 1, 2, and 3 does not actually givr very results compared to using a k-weight of 2 or 3 alone, though I'm willing to believe that there are cases where it can help find a solution for a fit with both low-Z and high-Z scatterers. That is, using multiple k-weights is a fine thing to do but it does not lower correlations between N and sigma2 (or E0 and R) by very much. Cheers, On Fri, Aug 27, 2021 at 7:41 PM Peng Liu wrote: > Dear Ifeffit members, > > I received the following two comments. > > " > Comment 1: Authors have fixed the amplitude reduction factor (SO2) to a > fixed value (0.85). This factor is specific to particular chemical compound > and sample preparation and quality (mostly homogeneity), measurement method > (e.g. absorption, fluorescence). Authors can find in literature [e.g. > Rehr2000] that SO2 for ideal samples (having no other effects) represent > multielectron effects, which by definition depend on valence and ligands. > Even more, SO2 is correlated with Debye-Waller factor (σ²) and coordination > number (CN), so any chosen value will be compensated by CN and σ². As > coordination numbers are used as quantitative indicators in discussion and > following conclusions. I would request to clarify the selection criteria > for SO2 values and advise to revise this approach (i.e. not to fix SO2 as > the same value for all samples). I do not expect drastic changes in > obtained CN values, but this should be tested. > > Comment 2: As I mentioned previously, coordination number (CN) is > correlated with Debye-Waller factor (σ²). My question is: how this > correlation is managed (eliminated)? Most probably (in FEFFIT) this is done > by using 3 separate values for n (1,2,3), where n is a power in expression > chi(k)*(k^n). > " > I used Artemis for the calculation. 1) Because S02 and CN are > multiplication relations in the EXAFS equation, as we usually do, we fixed > S02 to obtain CN for unknown samples. 2) there are outputs regarding the > correlation between different fitting parameters from Artemis. Is there a > way to manage or eliminate the correlation as the reviewer mentioned using > Artemis or Larch? > > If you also could give me some suggestions to answer the comments, that > would also be greatly appreciated. > > -- > Best Regards, > > Peng Liu > > School of Environmental Studies > > China University of Geosciences, Wuhan, Hubei Province, PR China > > https://scholar.google.com/citations?user=qUtyvokJ&hl=en > http://grzy.cug.edu.cn/049121/zh_CN/index.htm > ___ > Ifeffit mailing list > Ifeffit@millenia.cars.aps.anl.gov > http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit > Unsubscribe: http://millenia.cars.aps.anl.gov/mailman/options/ifeffit > ___ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit Unsubscribe: http://millenia.cars.aps.anl.gov/mailman/options/ifeffit
