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March 2015
- 22 participants
- 32 discussions
Hi everybody,
I wanted to report a really annoying problem for mac users. I’m running Athena on my laptop, on OSX 10.10 (Yosemite) with macports. I had to install also quartzX11 to be able to plot data (without it, it couldn’t find the DISPLAY value), but otherwise evrything went smoothly for a few days.
Then the first bug occured. I wasn’t able anymore to select any point on the plotting area to do normalization, I had to set the value in the boxes instead. It was annoying, but I could manage that. But now I have a much more disturbing issue.
Athena once crashed, (in the terminal, it was sait « Terminated 15 »), and every time I tried to launch it again, the same thing happens :
1) athena launch, a little bit longer than usual
2) a box appear to give me choice to recover data by importing it from autosave or not
3) I can’t select anaything and the rainbow wheel of death appears.
After a few hours, nothing changes… and I have to terminate the programm manually.
So I do some search on the internet and found thoses topics on the mailing list, and I tried thoses solutions :
https://www.mail-archive.com/ifeffit@millenia.cars.aps.anl.gov/msg04539.html <https://www.mail-archive.com/ifeffit@millenia.cars.aps.anl.gov/msg04539.html>
https://www.mail-archive.com/ifeffit%40millenia.cars.aps.anl.gov/msg04514.h… <https://www.mail-archive.com/ifeffit@millenia.cars.aps.anl.gov/msg04514.html>
I tried to find the autosave file : nothing
I tried to uninstall and reinstall macports : nothing
I tried to uninstall macports and install the demeter-devel : nothing
In demeter-devel, i tried to modify the athena.demeter_config file, by changing the autosave prompt box value from true to false, and despite being admin on ma mac, I’m not able to change antything in the file. So nothing works at this moment.
I will try again other solutions, but I will gladly accept any kind of help to solve my issues.
Thank you
ABBE J-Baptiste
4
7
Hi,
This may be a long shot, but
I was wondering if anyone is aware of EXAFS data on HCP Be. In particular
we are looking for Debye-Waller Factors, so a publication would be great,
but just data might work as well.
Thanks,
Josh Kas
2
1
Evaluation of uncertainty using correlated Debye model + advices for the fitting of an hexagonal Co-foil
by Samy OuldChikh 07 Apr '15
by Samy OuldChikh 07 Apr '15
07 Apr '15
Dear all,
I would like to go beyond the fitting of the first shell for a cobalt metallic foil acquired at FAME beamlime (ESRF).
It's not mandatory for the determination of So in this case, but I just would like to improve myself in EXAFS fitting.
The cobalt foil has an hexagonal structure (P 63/mmc, a =b=2.507 A, c= 4.068 A) according to the supplier.
The first 49 scattering paths calculated with FEFF were selected to cover the R range up to 5.1 A. This include multiple scattering paths.
The parametrization of those scattering paths is as follow (.apj enclosed) :
- Distances :
1) a spherical expansion term was used to describe distance variation in [hkl] direction (reff*alpha1) with l considered as "large" when compared to h,k (reff*alpha1)
2) another spherical expansion term was used to describe distance variation in pure [hk0] direction (reff*alpha2)
3) a rough average of two previous expansion terms for [hkl] direction when h,k are comparable to l (reff*(alpha2+alpha1)/2).
- For modeling disorder, the correlated Debye model was used with 3 parameters dt, dt2, dt3 (t =293K):
1) [hkl] direction with l considered as "large" : debye(t,dt)
2) pure [hk0] direction: debye(t,dt2)
3) for [hkl] direction with h,k comparable to l : debye(t,(dt+dt2)/2)
But does this choice of parametrization is really reasonable?
It seems very rough to me but when I look at the fit results it looks ok.
- Uncertainty on :
1) Distances : is it simply delta(r) = reff*delta(alpha) ?
2) Debye-Waller : I can't figure out how to relate the uncertainty computed for the Debye temperatures (dt, dt2) to the uncertainties of the debye-waller terms for each scattering paths. Although I spent some times trying to understand this paper, http://journals.aps.org/prb/pdf/10.1103/PhysRevB.20.4908, I can't write a simple relation at the end.
Many thanks for your kind help,
Best Regards,
Samy Ould-Chikh
KAUST Catalysis Center
Bldg.3,Level 4, #4231
4700 King Abdullah University of Science & Technology
Thuwal 23955-6900
Kingdom of Saudi Arabia
Tel: +966 12 8084486
E-mail: samy.ouldchikh(a)kaust.edu.sa
Website: http://kcc.kaust.edu.sa/Pages/Home.aspx
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2
3
Hello,
When I attempt to open Artemis on OSX Yosemite (10.10.2) the error message
copied below prints to the terminal. The initial image that indicates
Artemis is opening does appear, although Artemis fails to open. Athena and
Hephaestus open without error. Any suggestions as to how this could be
resolved would be appreciated.
Thanks,
George
$ artemis
Can't locate Math/Round.pm in @INC (@INC contains:
/opt/local/lib/perl5/site_perl/5.16.3/darwin-thread-multi-2level
/opt/local/lib/perl5/site_perl/5.16.3
/opt/local/lib/perl5/vendor_perl/5.16.3/darwin-thread-multi-2level
/opt/local/lib/perl5/vendor_perl/5.16.3
/opt/local/lib/perl5/5.16.3/darwin-thread-multi-2level
/opt/local/lib/perl5/5.16.3 /opt/local/lib/perl5/site_perl
/opt/local/lib/perl5/vendor_perl .) at
/opt/local/lib/perl5/site_perl/5.16.3/darwin-thread-multi-2level/Demeter/ScatteringPath.pm
line 44.
BEGIN failed--compilation aborted at
/opt/local/lib/perl5/site_perl/5.16.3/darwin-thread-multi-2level/Demeter/ScatteringPath.pm
line 44.
Compilation failed in require at
/opt/local/lib/perl5/site_perl/5.16.3/darwin-thread-multi-2level/Demeter.pm
line 306.
BEGIN failed--compilation aborted at
/opt/local/lib/perl5/site_perl/5.16.3/darwin-thread-multi-2level/Demeter/UI/Artemis.pm
line 26.
Compilation failed in require at /opt/local/bin/artemis line 34.
BEGIN failed--compilation aborted at /opt/local/bin/artemis line 34.
2
2
Dear all,
Today I helped a colleague install larch on OSX Yosemite but we ran into some problems using the source tarball from CARS (larch-0.9.24.tar.gz). It was a bit of a learning curve for me as a linux user but we managed to install the prerequisites (exept for epics) using macports and then ran the larch installer without noticing any warnings or errors. The problem after that was that we could not locate the larch binary. The source tarball does not include a 'bin' directory and some other things that are found in the github source so we went ahead and installed larch from the github source instead. After that we could locate the binery and start the interpreter. Did we make some mistake here or are there things missing in the source tarballs?
Best regards,
Johan Nilsson
2
2
Hi all,
I know this question has been asked for many times. S02 is expected to
be around, but smaller than 1, a fact that has been explained, such
as in the following previous emails, in our mailing list.
http://www.mail-archive.com/ifeffit%40millenia.cars.aps.anl.gov/msg02237.ht…
http://millenia.cars.aps.anl.gov/pipermail/ifeffit/2003-February/000230.html
However, I am continually get S02 value larger than 1 for a series of
similar samples when I fit data in Artemis. I think my fit is very
good, because my suspected model(based on other technique) could be
verified in XAFS analysis (i.e., defensible in physics), the
statistics is good ( R=0.01, reduced chi-square=31.4, fit-range:1.5~6
Angstrom, k-range: 3~14 angstrom-1) and all the parameters such as the
bond length, sigma2 are physically reasonable. The only thing makes me
uncomfortable is that parameter S02 keeps between 1.45 to 1.55 during
the fitting.
In my system, the absorber atom occupies two crystallographic sites.
So I built a model with paths generated from two FEFF calculations.
For paths generated from the 1st and 2nd FEFF calculation, the
amplitude parameters are set to be S02*P% and S02*(1-P%) respectively,
where P% is the first site occupancy percentage. Both S02 and P are
free parameters during the fit, and P is an important conclusion I
want to extract from XAFS fitting.
However, the fit result gives me S02=1.45 ~ 1.55 and P=0.51 ~ 0.56 all
the time (i.e., for each path the 'total amplitude' S02*P% or
S02*(1-P%) are about 0.7~0.8, smaller than 1). It looks to me that I
got a 'perfect' fit but I am not sure if S02 larger than one is
defensible. So I have to ask:
1) Is my current fit with S02 larger than one reasonable? If not, what
could be suggested to get around it?
2) What's the meaning of S02? It is interpreted in physics that it is
a reduced electron excitation parameter, but is it possible that S02
will be affected by any experimental condition?
3) Can anyone share whether you had the multiple site system that gets
S02 larger than one?
Looking forward to your help.
Best,
Yanyun
6
23
Dear all,
Has anybody succeeded with installing demeter from source on a Mac? I have attempted to install demeter from source on OS X 10.10.2, but so far without success.
I have followed the installation procedure for Installing source code at http://bruceravel.github.io/demeter/pods/installation.pod.html <http://bruceravel.github.io/demeter/pods/installation.pod.html>, except I installed pgplot from source instead of using the install script provided through ifeffit. I don’t get any errors installing either pgplot or ifeffit.
All dependencies for demeter should be met:
$ sudo perl ./Build.PL
Password:
Created MYMETA.yml and MYMETA.json
Creating new 'Build' script for 'Demeter' version '0.9.21'
If all dependencies are met, build and install Demeter by doing:
<snip>
The build seems to go fine:
$ sudo ./Build
Simple test for presence of gnuplot ---> found it! Using gnuplot with the x11 terminal.
Building Demeter
Building Artemis User's Guide
Building Athena User's Guide
But the tests fail miserably. Already before the actual testing starts, there is a message that loading of Ifeffit.bundle fails:
$ sudo ./Build test
t/000_ifeffit.t ......... Can't load '/Library/Perl/5.18/darwin-thread-multi-2level/auto/Ifeffit/Ifeffit.bundle' for module Ifeffit: dlopen(/Library/Perl/5.18/darwin-thread-multi-2level/auto/Ifeffit/Ifeffit.bundle, 2): Symbol not found: _ifeffit
Referenced from: /Library/Perl/5.18/darwin-thread-multi-2level/auto/Ifeffit/Ifeffit.bundle
Expected in: flat namespace
in /Library/Perl/5.18/darwin-thread-multi-2level/auto/Ifeffit/Ifeffit.bundle at /System/Library/Perl/5.18/darwin-thread-multi-2level/DynaLoader.pm line 194.
at t/000_ifeffit.t line 9.
Compilation failed in require at t/000_ifeffit.t line 9.
BEGIN failed--compilation aborted at t/000_ifeffit.t line 12.
# Looks like your test exited with 255 before it could output anything.
t/000_ifeffit.t ......... Dubious, test returned 255 (wstat 65280, 0xff00)
Failed 6/6 subtests
<snip>
However, the bundle exists:
$ ls -l /Library/Perl/5.18/darwin-thread-multi-2level/auto/Ifeffit/
total 152
-r-xr-xr-x 1 root wheel 76208 Mar 18 13:09 Ifeffit.bundle
and the symbol in question is part of the bundle (well, at least the string exists):
$ grep _ifeffit /Library/Perl/5.18/darwin-thread-multi-2level/auto/Ifeffit/*
Binary file /Library/Perl/5.18/darwin-thread-multi-2level/auto/Ifeffit/Ifeffit.bundle matches
Does anybody know what is going on? Am I missing something?
A couple of more bits of information:
$ which ifeffit
/usr/local/bin/ifeffit
$ ifeffit
Ifeffit 1.2.12 Copyright (c) 2005 Matt Newville, Univ of Chicago
command-line shell version 1.1 with GNU Readline
Ifeffit> testplot
%PGPLOT, Unrecognized device type
%PGPLOT, Invalid device specification: /AQT
%PGPLOT, PGBBUF: selected graphics device is not open
%PGPLOT, PGQCI: selected graphics device is not open
%PGPLOT, PGQFS: selected graphics device is not open
%PGPLOT, PGSCI: selected graphics device is not open
%PGPLOT, PGSFS: selected graphics device is not open
%PGPLOT, PGSVP: selected graphics device is not open
%PGPLOT, PGBBUF: selected graphics device is not open
%PGPLOT, PGEBUF: selected graphics device is not open
%PGPLOT, PGSVP: selected graphics device is not open
%PGPLOT, PGSCI: selected graphics device is not open
%PGPLOT, PGSFS: selected graphics device is not open
%PGPLOT, PGEBUF: selected graphics device is not open
** plot error: cannot open device:
%PGPLOT, Unrecognized device type
%PGPLOT, Invalid device specification: /AQT
** plot error: cannot open device:
Ifeffit> exit
$ which athena
/usr/local/bin/athena
$ athena
dyld: lazy symbol binding failed: Symbol not found: _iff_exec
Referenced from: /Library/Perl/5.18/darwin-thread-multi-2level/auto/Ifeffit/Ifeffit.bundle
Expected in: flat namespace
dyld: Symbol not found: _iff_exec
Referenced from: /Library/Perl/5.18/darwin-thread-multi-2level/auto/Ifeffit/Ifeffit.bundle
Expected in: flat namespace
Trace/BPT trap: 5
Regards,
Anders
3
7
Re: [Ifeffit] Breaking down correlationships between parameters
by Rana, Jatinkumar Kantilal 23 Mar '15
by Rana, Jatinkumar Kantilal 23 Mar '15
23 Mar '15
Hi Bruce,
Thanks for your comments and links of your lectures. I forgot to mention that I use Artemis for fitting my data.
Best regards,
Jatin
-----Original Message-----
From: ifeffit-bounces(a)millenia.cars.aps.anl.gov [mailto:ifeffit-bounces@millenia.cars.aps.anl.gov] On Behalf Of ifeffit-request(a)millenia.cars.aps.anl.gov
Sent: 23 March, 2015 15:37
To: ifeffit(a)millenia.cars.aps.anl.gov
Subject: Ifeffit Digest, Vol 145, Issue 45
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Today's Topics:
1. Re: Breaking down correlationships between parameters
(Bruce Ravel)
2. Re: Breaking down correlationships between parameters
(Rana, Jatinkumar Kantilal)
----------------------------------------------------------------------
Message: 1
Date: Mon, 23 Mar 2015 09:27:05 -0400
From: Bruce Ravel <bravel(a)bnl.gov>
To: XAFS Analysis using Ifeffit <ifeffit(a)millenia.cars.aps.anl.gov>
Subject: Re: [Ifeffit] Breaking down correlationships between
parameters
Message-ID: <551014A9.4090604(a)bnl.gov>
Content-Type: text/plain; charset=utf-8; format=flowed
On 03/23/2015 08:54 AM, Rana, Jatinkumar Kantilal wrote:
> The term N*S02 is fitted for each path of the FEFF calculation. So my
> question is, even if we know N with a great certainty for some path,
> how can we vary both N and S02 for other paths ? or Did I understand
> it wrong ?
At no point in your emails did you say that you are using Artemis to do your fitting. The comment I am about to make may not, therefore, be relevant to you.
In Ifeffit and Larch -- and therefore in Artemis -- we DO NOT fit N*SO2.
Fits in Ifeffit, Larch, and Artemis use a set of user-defined parameters as the variables of the fit. As part of the fitting model, the user relates the variables of the fit to the parameters of the EXAFS equation using math expression.
This benefit of the generality of the fitting model allows the user to easily encode prior knowledge into a fit. The cost is that the parameters have to be interpreted in some kind of physical context.
To answer you question specifically, Artemis allows you to set or float parameters for N and S02 and to define the amplitude term of the EXAFS equation for each path in any way that you see fit. In that way, you can implement all the suggestions that Matt, Scott, and Chris have made.
I discuss this in some detail starting at page 35 of this presentation.
https://speakerdeck.com/bruceravel/advanced-topics-in-exafs-analysis
Among the lectures at
http://www.diamond.ac.uk/Beamlines/Spectroscopy/Techniques/XAS.html,
this is the one called "Fit Evaluation and Fitting multiple structures".
HTH,
B
--
Bruce Ravel ------------------------------------ bravel(a)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/
------------------------------
Message: 2
Date: Mon, 23 Mar 2015 14:36:31 +0000
From: "Rana, Jatinkumar Kantilal"
<jatinkumar.rana(a)helmholtz-berlin.de>
To: "ifeffit(a)millenia.cars.aps.anl.gov"
<ifeffit(a)millenia.cars.aps.anl.gov>
Subject: Re: [Ifeffit] Breaking down correlationships between
parameters
Message-ID: <DA4C7D90F90BC249A03505C87F2EB8AB230EE7F0@didag1>
Content-Type: text/plain; charset="utf-8"
Hi Scott,
Thanks for your explanation. It means the reverse can also be true, i.e., I can guess N1 (nearest-neighbors in the first shell) and S02 by setting N2, N3 and N4 to values known from other analysis. I did a quick check by fitting the data.
I conducted two fits:
1) setting S02 and guessing only N1
2) guessing both N1 and S02.
To my surprise, both the fits gave very similar results, except that the fit#1 refined value of N1 to a higher side, while fit#2 estimated N1 closer to a physically reasonable value (as expected).
I always constrained S02 when refining N for any path, due to 100% correlation between them. However, I am surprised to know that they can be refined independently.
Best regards,
Jatin
-----Original Message-----
From: ifeffit-bounces(a)millenia.cars.aps.anl.gov [mailto:ifeffit-bounces@millenia.cars.aps.anl.gov] On Behalf Of ifeffit-request(a)millenia.cars.aps.anl.gov
Sent: 23 March, 2015 14:19
To: ifeffit(a)millenia.cars.aps.anl.gov
Subject: Ifeffit Digest, Vol 145, Issue 44
Send Ifeffit mailing list submissions to
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Today's Topics:
1. Re: Breaking down correlationships between parameters
(Scott Calvin)
----------------------------------------------------------------------
Message: 1
Date: Mon, 23 Mar 2015 09:18:21 -0400
From: Scott Calvin <scalvin(a)sarahlawrence.edu>
To: XAFS Analysis using Ifeffit <ifeffit(a)millenia.cars.aps.anl.gov>
Subject: Re: [Ifeffit] Breaking down correlationships between
parameters
Message-ID: <78C1636C-91CF-4C8C-9D48-3EC361BB7237(a)slc.edu>
Content-Type: text/plain; charset="utf-8"
Hi Jatin,
The key is that S02 should be the same for all paths.
For example:
Suppose you are very confident path 1 has a coordination number of 6, because of prior knowledge you have about the system. Paths 2, 3, and 4 have unknown coordination numbers, however.
N1 (i.e. the degeneracy of path 1) you set to 6.
You guess S02, N2, N3, and N4. Of course, the way Artemis and Ifeffit implement that, you're writing N1*S02 for the S02 field of Path 1, N2*S02 for the S02 field of Path 2, etc., and then setting N1 = 6 and guessing S02, N2, N3, and N4.
There is now enough information for S02, N2, N3, and N4 to each be fitted without 100% correlation.
?Scott Calvin
Sarah Lawrence College
> On Mar 23, 2015, at 8:54 AM, Rana, Jatinkumar Kantilal <jatinkumar.rana(a)helmholtz-berlin.de> wrote:
>
> Hi Chris,
>
> The term N*S02 is fitted for each path of the FEFF calculation. So my question is, even if we know N with a great certainty for some path, how can we vary both N and S02 for other paths ? or Did I understand it wrong ?
>
> Best regards,
> Jatin
>
> -----Original Message-----
> From: ifeffit-bounces(a)millenia.cars.aps.anl.gov
> [mailto:ifeffit-bounces@millenia.cars.aps.anl.gov] On Behalf Of
> ifeffit-request(a)millenia.cars.aps.anl.gov
> Sent: 23 March, 2015 12:16
> To: ifeffit(a)millenia.cars.aps.anl.gov
> Subject: Ifeffit Digest, Vol 145, Issue 42
>
> Send Ifeffit mailing list submissions to
> ifeffit(a)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-request(a)millenia.cars.aps.anl.gov
>
> You can reach the person managing the list at
> ifeffit-owner(a)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: Breaking down correlationships between parameters
> (Rana, Jatinkumar Kantilal)
> 2. Re: Breaking down correlationships between parameters
> (Chris Patridge)
>
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Mon, 23 Mar 2015 11:00:19 +0000
> From: "Rana, Jatinkumar Kantilal"
> <jatinkumar.rana(a)helmholtz-berlin.de>
> To: "ifeffit(a)millenia.cars.aps.anl.gov"
> <ifeffit(a)millenia.cars.aps.anl.gov>
> Subject: Re: [Ifeffit] Breaking down correlationships between
> parameters
> Message-ID: <DA4C7D90F90BC249A03505C87F2EB8AB230EE777@didag1>
> Content-Type: text/plain; charset="utf-8"
>
> Hi Scott,
>
> Thank you for your comments. Can you please elaborate a little bit more on this "In cases like that, both N for all paths but one and S02 can be fit without 100% correlation."
>
> Best regards,
> Jatin
>
> -----Original Message-----
> From: ifeffit-bounces(a)millenia.cars.aps.anl.gov
> [mailto:ifeffit-bounces@millenia.cars.aps.anl.gov] On Behalf Of
> ifeffit-request(a)millenia.cars.aps.anl.gov
> Sent: 23 March, 2015 10:16
> To: ifeffit(a)millenia.cars.aps.anl.gov
> Subject: Ifeffit Digest, Vol 145, Issue 41
>
> Send Ifeffit mailing list submissions to
> ifeffit(a)millenia.cars.aps.anl.gov
>
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> When replying, please edit your Subject line so it is more specific than "Re: Contents of Ifeffit digest..."
>
>
> Today's Topics:
>
> 1. Re: Breaking down correlationships between parameters
> (Scott Calvin)
> 2. Re: Breaking down correlationships between parameters
> (Matt Newville)
> 3. Re: Breaking down correlationships between parameters
> (Rana, Jatinkumar Kantilal)
>
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Sun, 22 Mar 2015 13:44:28 -0400
> From: Scott Calvin <scalvin(a)sarahlawrence.edu>
> To: XAFS Analysis using Ifeffit <ifeffit(a)millenia.cars.aps.anl.gov>
> Subject: Re: [Ifeffit] Breaking down correlationships between
> parameters
> Message-ID: <E0C66911-7AD2-448C-9F64-F03E262D04D7(a)slc.edu>
> Content-Type: text/plain; charset="utf-8"
>
> One side-comment from me:
>
> On Mar 22, 2015, at 12:52 PM, Matt Newville <newville(a)cars.uchicago.edu<mailto:newville@cars.uchicago.edu>> wrote:
>
> N and S02 are always 100% correlated (mathematically, not merely by the finite k range).
>
> Matt is saying that N and S02 are always 100% correlated for a single path. But in some situations you might know N for one path but not others. For example, you might know that the absorbing atom is octahedrally coordinated to oxygen but not be as certain as to next-nearest neighbors, or that there are copper atoms on the corners of a simple cubic lattice with a mixture of atoms at other positions. In cases like that, both N for all paths but one and S02 can be fit without 100% correlation.
>
> The degeneracy of multiple-scattering paths can often be constrained in terms of the coordination numbers for direct-scattering paths, which can further reduce (not ?break?) the correlation.
>
> In terms of the main question, I agree with Matt: I don?t think there?s much point in using the line-crossing technique nowadays; fitting using multiple k-weights simultaneously accomplishes the same thing but is a bit easier to interpret statistically.
>
> ?Scott Calvin
> Sarah Lawrence College
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> ------------------------------
>
> Message: 2
> Date: Sun, 22 Mar 2015 15:56:20 -0500
> From: Matt Newville <newville(a)cars.uchicago.edu>
> To: XAFS Analysis using Ifeffit <ifeffit(a)millenia.cars.aps.anl.gov>
> Subject: Re: [Ifeffit] Breaking down correlationships between
> parameters
> Message-ID:
>
> <CA+7ESbq_s0X3L9rPDDnwAdhx7h6Ptx5-8guCUFTM2OjwkYEerA(a)mail.gmail.com>
> Content-Type: text/plain; charset="utf-8"
>
> On Sun, Mar 22, 2015 at 12:44 PM, Scott Calvin
> <scalvin(a)sarahlawrence.edu>
> wrote:
>
>> One side-comment from me:
>>
>> On Mar 22, 2015, at 12:52 PM, Matt Newville
>> <newville(a)cars.uchicago.edu>
>> wrote:
>>
>> N and S02 are always 100% correlated (mathematically, not merely by
>> the finite k range).
>>
>>
>> Matt is saying that N and S02 are always 100% correlated *for a
>> single path*. But in some situations you might know N for one path
>> but not others. For example, you might know that the absorbing atom
>> is octahedrally coordinated to oxygen but not be as certain as to
>> next-nearest neighbors, or that there are copper atoms on the corners
>> of a simple cubic lattice with a mixture of atoms at other positions.
>> In cases like that, both N for all paths but one and S02 can be fit without 100% correlation.
>>
>>
> Yes, I completely agree with Scott -- this is a good point that I
> neglected. In addition to looking at multiple shells, one might also
> consider using temperature or pressure dependence to separate N*S02 and
> sigma2. Those aren't without assumptions, and still don't remove the
> inherent correlation, but are useful approaches.
>
> The degeneracy of multiple-scattering paths can often be constrained
> in
>> terms of the coordination numbers for direct-scattering paths, which
>> can further reduce (not ?break?) the correlation.
>>
>> In terms of the main question, I agree with Matt: I don?t think
>> there?s much point in using the line-crossing technique nowadays;
>> fitting using multiple k-weights simultaneously accomplishes the same
>> thing but is a bit easier to interpret statistically.
>>
>> ?Scott Calvin
>> Sarah Lawrence College
>>
>> _______________________________________________
>> Ifeffit mailing list
>> Ifeffit(a)millenia.cars.aps.anl.gov
>> http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
>>
>>
> --Matt
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>
> ------------------------------
>
> Message: 3
> Date: Mon, 23 Mar 2015 09:16:02 +0000
> From: "Rana, Jatinkumar Kantilal"
> <jatinkumar.rana(a)helmholtz-berlin.de>
> To: "ifeffit(a)millenia.cars.aps.anl.gov"
> <ifeffit(a)millenia.cars.aps.anl.gov>
> Subject: Re: [Ifeffit] Breaking down correlationships between
> parameters
> Message-ID: <DA4C7D90F90BC249A03505C87F2EB8AB230EE755@didag1>
> Content-Type: text/plain; charset="utf-8"
>
> Hi Matt,
>
> Thank you very much for your detailed explanation. As you pointed out that this approach ignores the statistical significance of fits and assumes that all fits are "good" fits. Also, the point that this approach yields a value of the parameter which is only slightly less correlated with the other one, but not completely removes the correlation. It makes it really clear to me that how this approach works and what are the pros and cons.
>
> Well, I myself has never tried this approach of minimizing the correlation between N*S02 and sigma2, but I read a lot about it in the literature. With my limited knowledge about the method, I could not judge this approach, although I had my own doubts.
>
> I truly appreciate your efforts in providing me a deeper insight into this approach.
>
> Best regards,
> Jatin
>
> -----Original Message-----
> From: ifeffit-bounces(a)millenia.cars.aps.anl.gov
> [mailto:ifeffit-bounces@millenia.cars.aps.anl.gov] On Behalf Of
> ifeffit-request(a)millenia.cars.aps.anl.gov
> Sent: 22 March, 2015 18:00
> To: ifeffit(a)millenia.cars.aps.anl.gov
> Subject: Ifeffit Digest, Vol 145, Issue 40
>
> Send Ifeffit mailing list submissions to
> ifeffit(a)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-request(a)millenia.cars.aps.anl.gov
>
> You can reach the person managing the list at
> ifeffit-owner(a)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: Breaking down correlationships between parameters
> (Matt Newville)
>
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Sun, 22 Mar 2015 11:52:30 -0500
> From: Matt Newville <newville(a)cars.uchicago.edu>
> To: XAFS Analysis using Ifeffit <ifeffit(a)millenia.cars.aps.anl.gov>
> Subject: Re: [Ifeffit] Breaking down correlationships between
> parameters
> Message-ID:
>
> <CA+7ESbqcyQHf9XUh2uhk=Lv09An7E9LXxqDTX-X6kRJHy9PFzw(a)mail.gmail.com>
> Content-Type: text/plain; charset="utf-8"
>
> Hi Jatin,
>
>
> On Sat, Mar 21, 2015 at 10:41 AM, Rana, Jatinkumar Kantilal < jatinkumar.rana(a)helmholtz-berlin.de> wrote:
>
>> Hi Matt,
>>
>> Thanks a lot for your prompt reply. The method I am referring to is
>> not the multiple k-weight fits by constraining N*S02. My apologies
>> for not being clear enough. Let's do it again. I am actually
>> referring to an approach where we take an advantage of a different
>> k-dependence of various parameters to breakdown correlations between
>> them. For example, S02 and sigma2. S02 is k-independent and Sigma2 has k^2 dependence.
>>
>>
> Yes, I am familiar with this approach, and I understand that this is what you are using. What I am saying is that this does not work nearly as well as (sometimes) claimed, and is sort of cheating. It ignores the measures of statistical significance.
>
> In this case, to breakdown correlation between S02 and sigma2,
>
>
> The correlation between N*S02 and sigma2 is inherent to the finite k-range of the EXAFS signal. It cannot be "broken", though it might be reduced.
>
>
>> one can assume a series of S02 values and perform fits using a single
>> k-weight each time (say k-weight 1,2 and 3) and record corresponding
>> sigma2 values.
>
> Let us say for k-weight =1, a series of preset S02 values will result
> in a
>> series of corresponding sigma2 values refined in fits, which can be
>> plotted as a straight line in sigma2 vs. S02 plot.
>
>
> OK, one can fit sigma2 with a series of preset values on N*S02. That's fine. But it does NOT lead to an infinitely thin line of sigma2 vs.
> N*S02. Each sigma2 value on that line has a width, corresponding to its
> uncertainty. In fact, the line you produce nicely demonstrates and
> measures the correlation of N*S02 and sigma2 as the slope of this line.
>
>
>> Similar straight lines can be obtained for fits using k-weight = 2
>> and then 3.
>
> Now, these three lines may intersect at or near some point, which will
>> determine the "true" value of parameters independent of k-weight.
>
>
> The different lines (each with finite thickness) will give a *range of
> values* for N*S02 and sigma2, not a single value.
>
> The biggest problem with this approach is that it ignores the relative goodness-of-fits (let's just assume that is 'chi-square' for the purpose of
> this discussion) for the fits along these lines. Some fits are better
> than others, and this approach completely ignores that fact, and equally importantly ignores the fact that there is a range of values for chi-square
> that are consistent with "good". If you include these values, your
> linear plot will become contours of chi-square as a function of N*S02 and
> sigma2. And, yes, by using different k-weights and k-ranges and so on you
> can get overlapping contour plots which may reduce the correlation a small amount when looked at as an ensemble. And you can find a best set of values for N*S02 and sigma2, but *each* of these will have an uncertainty.
>
> So, you can use this approach to find a good value for N*S02, but it is not breaking the correlation. You can do this by hand. Or you can just do a
> fit with datasets with different k-weights and k-ranges. When you do this
> as a fit, you will see that the correlation is still fairly large.
>
> Also, just to be clear, this is absolutely not a "true" value. It is a measured value. Not at all the same thing.
>
> One can then constrain S02 to a value obtained from the point of
>> intersection of three lines and vary sigma2 in a fit.
>
>
> Well, one can certainly set N*S02 to some value and fit sigma2. As I said earlier, this ignores the correlation of N*S02 and sigma2, but does not remove that correlation.
>
>
>> In this particular case, however, the advantage is, S02 does not
>> depend on changes inside sample and we have very good estimate of its
>> range (say 0.7
>> - 1.0).
>>
>> Now suppose instead of S02 (which i now set to a reasonable value), I
>> am interested in determining N, but it is highly correlated with
>> sigma2. Each time when disorder in the sample increases, the sigma2
>> increases and due to its high correlation, N is also overestimated.
>> On the other hand, when the disorder in the sample decreases, the
>> sigma2 decreases and I can have a "true" estimation of N in the
>> sample. Can I still apply the above mentioned approach to break the correlationship between N and sigma2 and get a "true"
>> estimation of N, even if disorder is high in my samples ? or it is
>> simply not possible due to the fact that both N and sigma2 varies
>> with changes inside the sample.
>>
>>
> N and S02 are always 100% correlated (mathematically, not merely by the finite k range). So, to the extent that the approach works at all, you can use it for "N" or "S02". Really, the approach is comparing N*S02 and sigma2, in one case you asserted a value of "N" and projected all changes to "S02" -- you can equally assert "S02" and project all changes to "N".
>
> To be clear, this is not going to find the "true" value of anything, because no analysis is ever going to find the "true" value -- it's going to find a measured value.
>
> Finally, the correlation of N*S02 and sigma2 does not imply a bias in the values for N*S02. N*S02 is NOT overestimated because it is highly correlated with sigma2.
>
> Hope that helps,
>
> --Matt
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>
> _______________________________________________
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>
> End of Ifeffit Digest, Vol 145, Issue 40
> ****************************************
>
> ________________________________
>
> Helmholtz-Zentrum Berlin f?r Materialien und Energie GmbH
>
> Mitglied der Hermann von Helmholtz-Gemeinschaft Deutscher Forschungszentren e.V.
>
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> stv. Vorsitzende Dr. Beatrix Vierkorn-Rudolph
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>
> Sitz Berlin, AG Charlottenburg, 89 HRB 5583
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> ------------------------------
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> http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
>
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> End of Ifeffit Digest, Vol 145, Issue 41
> ****************************************
>
> ________________________________
>
> Helmholtz-Zentrum Berlin f?r Materialien und Energie GmbH
>
> Mitglied der Hermann von Helmholtz-Gemeinschaft Deutscher Forschungszentren e.V.
>
> Aufsichtsrat: Vorsitzender Prof. Dr. Dr. h.c. mult. Joachim Treusch,
> stv. Vorsitzende Dr. Beatrix Vierkorn-Rudolph
> Gesch?ftsf?hrung: Prof. Dr. Anke Rita Kaysser-Pyzalla, Thomas
> Frederking
>
> Sitz Berlin, AG Charlottenburg, 89 HRB 5583
>
> Postadresse:
> Hahn-Meitner-Platz 1
> D-14109 Berlin
>
> http://www.helmholtz-berlin.de
>
>
>
> ------------------------------
>
> Message: 2
> Date: Mon, 23 Mar 2015 07:15:05 -0400
> From: Chris Patridge <patridge(a)buffalo.edu>
> To: XAFS Analysis using Ifeffit <ifeffit(a)millenia.cars.aps.anl.gov>
> Subject: Re: [Ifeffit] Breaking down correlationships between
> parameters
> Message-ID: <29942DF9-8043-424E-BDCC-9CA19EB4AC9B(a)buffalo.edu>
> Content-Type: text/plain; charset=utf-8
>
> I think Scott was pointing out that first neighbors may be known with high certainty and therefore you can set this value thereby removing it and slightly reducing the correlations.
>
> Chris
>
> Sent from my iPhone
>
>> On Mar 23, 2015, at 7:00 AM, Rana, Jatinkumar Kantilal <jatinkumar.rana(a)helmholtz-berlin.de> wrote:
>>
>> Hi Scott,
>>
>> Thank you for your comments. Can you please elaborate a little bit more on this "In cases like that, both N for all paths but one and S02 can be fit without 100% correlation."
>>
>> Best regards,
>> Jatin
>>
>> -----Original Message-----
>> From: ifeffit-bounces(a)millenia.cars.aps.anl.gov
>> [mailto:ifeffit-bounces@millenia.cars.aps.anl.gov] On Behalf Of
>> ifeffit-request(a)millenia.cars.aps.anl.gov
>> Sent: 23 March, 2015 10:16
>> To: ifeffit(a)millenia.cars.aps.anl.gov
>> Subject: Ifeffit Digest, Vol 145, Issue 41
>>
>> Send Ifeffit mailing list submissions to
>> ifeffit(a)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-request(a)millenia.cars.aps.anl.gov
>>
>> You can reach the person managing the list at
>> ifeffit-owner(a)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: Breaking down correlationships between parameters
>> (Scott Calvin)
>> 2. Re: Breaking down correlationships between parameters
>> (Matt Newville)
>> 3. Re: Breaking down correlationships between parameters
>> (Rana, Jatinkumar Kantilal)
>>
>>
>> ---------------------------------------------------------------------
>> -
>>
>> Message: 1
>> Date: Sun, 22 Mar 2015 13:44:28 -0400
>> From: Scott Calvin <scalvin(a)sarahlawrence.edu>
>> To: XAFS Analysis using Ifeffit <ifeffit(a)millenia.cars.aps.anl.gov>
>> Subject: Re: [Ifeffit] Breaking down correlationships between
>> parameters
>> Message-ID: <E0C66911-7AD2-448C-9F64-F03E262D04D7(a)slc.edu>
>> Content-Type: text/plain; charset="utf-8"
>>
>> One side-comment from me:
>>
>> On Mar 22, 2015, at 12:52 PM, Matt Newville <newville(a)cars.uchicago.edu<mailto:newville@cars.uchicago.edu>> wrote:
>>
>> N and S02 are always 100% correlated (mathematically, not merely by the finite k range).
>>
>> Matt is saying that N and S02 are always 100% correlated for a single path. But in some situations you might know N for one path but not others. For example, you might know that the absorbing atom is octahedrally coordinated to oxygen but not be as certain as to next-nearest neighbors, or that there are copper atoms on the corners of a simple cubic lattice with a mixture of atoms at other positions. In cases like that, both N for all paths but one and S02 can be fit without 100% correlation.
>>
>> The degeneracy of multiple-scattering paths can often be constrained in terms of the coordination numbers for direct-scattering paths, which can further reduce (not ?break?) the correlation.
>>
>> In terms of the main question, I agree with Matt: I don?t think there?s much point in using the line-crossing technique nowadays; fitting using multiple k-weights simultaneously accomplishes the same thing but is a bit easier to interpret statistically.
>>
>> ?Scott Calvin
>> Sarah Lawrence College
>> -------------- next part -------------- An HTML attachment was
>> scrubbed...
>> URL:
>> <http://millenia.cars.aps.anl.gov/pipermail/ifeffit/attachments/20150
>> 3
>> 22/f4e7b7e4/attachment-0001.htm>
>>
>> ------------------------------
>>
>> Message: 2
>> Date: Sun, 22 Mar 2015 15:56:20 -0500
>> From: Matt Newville <newville(a)cars.uchicago.edu>
>> To: XAFS Analysis using Ifeffit <ifeffit(a)millenia.cars.aps.anl.gov>
>> Subject: Re: [Ifeffit] Breaking down correlationships between
>> parameters
>> Message-ID:
>>
>> <CA+7ESbq_s0X3L9rPDDnwAdhx7h6Ptx5-8guCUFTM2OjwkYEerA(a)mail.gmail.com>
>> Content-Type: text/plain; charset="utf-8"
>>
>> On Sun, Mar 22, 2015 at 12:44 PM, Scott Calvin
>> <scalvin(a)sarahlawrence.edu>
>> wrote:
>>
>>> One side-comment from me:
>>>
>>> On Mar 22, 2015, at 12:52 PM, Matt Newville
>>> <newville(a)cars.uchicago.edu>
>>> wrote:
>>>
>>> N and S02 are always 100% correlated (mathematically, not merely by
>>> the finite k range).
>>>
>>>
>>> Matt is saying that N and S02 are always 100% correlated *for a
>>> single path*. But in some situations you might know N for one path
>>> but not others. For example, you might know that the absorbing atom
>>> is octahedrally coordinated to oxygen but not be as certain as to
>>> next-nearest neighbors, or that there are copper atoms on the
>>> corners of a simple cubic lattice with a mixture of atoms at other positions.
>>> In cases like that, both N for all paths but one and S02 can be fit without 100% correlation.
>> Yes, I completely agree with Scott -- this is a good point that I
>> neglected. In addition to looking at multiple shells, one might also
>> consider using temperature or pressure dependence to separate N*S02 and
>> sigma2. Those aren't without assumptions, and still don't remove the
>> inherent correlation, but are useful approaches.
>>
>> The degeneracy of multiple-scattering paths can often be constrained
>> in
>>> terms of the coordination numbers for direct-scattering paths, which
>>> can further reduce (not ?break?) the correlation.
>>>
>>> In terms of the main question, I agree with Matt: I don?t think
>>> there?s much point in using the line-crossing technique nowadays;
>>> fitting using multiple k-weights simultaneously accomplishes the
>>> same thing but is a bit easier to interpret statistically.
>>>
>>> ?Scott Calvin
>>> Sarah Lawrence College
>>>
>>> _______________________________________________
>>> Ifeffit mailing list
>>> Ifeffit(a)millenia.cars.aps.anl.gov
>>> http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
>> --Matt
>> -------------- next part -------------- An HTML attachment was
>> scrubbed...
>> URL:
>> <http://millenia.cars.aps.anl.gov/pipermail/ifeffit/attachments/20150
>> 3
>> 22/3dd3f763/attachment-0001.htm>
>>
>> ------------------------------
>>
>> Message: 3
>> Date: Mon, 23 Mar 2015 09:16:02 +0000
>> From: "Rana, Jatinkumar Kantilal"
>> <jatinkumar.rana(a)helmholtz-berlin.de>
>> To: "ifeffit(a)millenia.cars.aps.anl.gov"
>> <ifeffit(a)millenia.cars.aps.anl.gov>
>> Subject: Re: [Ifeffit] Breaking down correlationships between
>> parameters
>> Message-ID: <DA4C7D90F90BC249A03505C87F2EB8AB230EE755@didag1>
>> Content-Type: text/plain; charset="utf-8"
>>
>> Hi Matt,
>>
>> Thank you very much for your detailed explanation. As you pointed out that this approach ignores the statistical significance of fits and assumes that all fits are "good" fits. Also, the point that this approach yields a value of the parameter which is only slightly less correlated with the other one, but not completely removes the correlation. It makes it really clear to me that how this approach works and what are the pros and cons.
>>
>> Well, I myself has never tried this approach of minimizing the correlation between N*S02 and sigma2, but I read a lot about it in the literature. With my limited knowledge about the method, I could not judge this approach, although I had my own doubts.
>>
>> I truly appreciate your efforts in providing me a deeper insight into this approach.
>>
>> Best regards,
>> Jatin
>>
>> -----Original Message-----
>> From: ifeffit-bounces(a)millenia.cars.aps.anl.gov
>> [mailto:ifeffit-bounces@millenia.cars.aps.anl.gov] On Behalf Of
>> ifeffit-request(a)millenia.cars.aps.anl.gov
>> Sent: 22 March, 2015 18:00
>> To: ifeffit(a)millenia.cars.aps.anl.gov
>> Subject: Ifeffit Digest, Vol 145, Issue 40
>>
>> Send Ifeffit mailing list submissions to
>> ifeffit(a)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-request(a)millenia.cars.aps.anl.gov
>>
>> You can reach the person managing the list at
>> ifeffit-owner(a)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: Breaking down correlationships between parameters
>> (Matt Newville)
>>
>>
>> ---------------------------------------------------------------------
>> -
>>
>> Message: 1
>> Date: Sun, 22 Mar 2015 11:52:30 -0500
>> From: Matt Newville <newville(a)cars.uchicago.edu>
>> To: XAFS Analysis using Ifeffit <ifeffit(a)millenia.cars.aps.anl.gov>
>> Subject: Re: [Ifeffit] Breaking down correlationships between
>> parameters
>> Message-ID:
>>
>> <CA+7ESbqcyQHf9XUh2uhk=Lv09An7E9LXxqDTX-X6kRJHy9PFzw(a)mail.gmail.com>
>> Content-Type: text/plain; charset="utf-8"
>>
>> Hi Jatin,
>>
>>
>>> On Sat, Mar 21, 2015 at 10:41 AM, Rana, Jatinkumar Kantilal < jatinkumar.rana(a)helmholtz-berlin.de> wrote:
>>>
>>> Hi Matt,
>>>
>>> Thanks a lot for your prompt reply. The method I am referring to is
>>> not the multiple k-weight fits by constraining N*S02. My apologies
>>> for not being clear enough. Let's do it again. I am actually
>>> referring to an approach where we take an advantage of a different
>>> k-dependence of various parameters to breakdown correlations between
>>> them. For example, S02 and sigma2. S02 is k-independent and Sigma2 has k^2 dependence.
>> Yes, I am familiar with this approach, and I understand that this is what you are using. What I am saying is that this does not work nearly as well as (sometimes) claimed, and is sort of cheating. It ignores the measures of statistical significance.
>>
>> In this case, to breakdown correlation between S02 and sigma2,
>>
>>
>> The correlation between N*S02 and sigma2 is inherent to the finite k-range of the EXAFS signal. It cannot be "broken", though it might be reduced.
>>
>>
>>> one can assume a series of S02 values and perform fits using a
>>> single k-weight each time (say k-weight 1,2 and 3) and record
>>> corresponding
>>> sigma2 values.
>>
>> Let us say for k-weight =1, a series of preset S02 values will result
>> in a
>>> series of corresponding sigma2 values refined in fits, which can be
>>> plotted as a straight line in sigma2 vs. S02 plot.
>>
>>
>> OK, one can fit sigma2 with a series of preset values on N*S02. That's fine. But it does NOT lead to an infinitely thin line of sigma2 vs.
>> N*S02. Each sigma2 value on that line has a width, corresponding to its
>> uncertainty. In fact, the line you produce nicely demonstrates and
>> measures the correlation of N*S02 and sigma2 as the slope of this line.
>>
>>
>>> Similar straight lines can be obtained for fits using k-weight = 2
>>> and then 3.
>>
>> Now, these three lines may intersect at or near some point, which
>> will
>>> determine the "true" value of parameters independent of k-weight.
>>
>>
>> The different lines (each with finite thickness) will give a *range
>> of
>> values* for N*S02 and sigma2, not a single value.
>>
>> The biggest problem with this approach is that it ignores the relative goodness-of-fits (let's just assume that is 'chi-square' for the purpose of
>> this discussion) for the fits along these lines. Some fits are better
>> than others, and this approach completely ignores that fact, and equally importantly ignores the fact that there is a range of values for chi-square
>> that are consistent with "good". If you include these values, your
>> linear plot will become contours of chi-square as a function of N*S02 and
>> sigma2. And, yes, by using different k-weights and k-ranges and so on you
>> can get overlapping contour plots which may reduce the correlation a small amount when looked at as an ensemble. And you can find a best set of values for N*S02 and sigma2, but *each* of these will have an uncertainty.
>>
>> So, you can use this approach to find a good value for N*S02, but it is not breaking the correlation. You can do this by hand. Or you can just do a
>> fit with datasets with different k-weights and k-ranges. When you do this
>> as a fit, you will see that the correlation is still fairly large.
>>
>> Also, just to be clear, this is absolutely not a "true" value. It is a measured value. Not at all the same thing.
>>
>> One can then constrain S02 to a value obtained from the point of
>>> intersection of three lines and vary sigma2 in a fit.
>>
>>
>> Well, one can certainly set N*S02 to some value and fit sigma2. As I said earlier, this ignores the correlation of N*S02 and sigma2, but does not remove that correlation.
>>
>>
>>> In this particular case, however, the advantage is, S02 does not
>>> depend on changes inside sample and we have very good estimate of
>>> its range (say 0.7
>>> - 1.0).
>>>
>>> Now suppose instead of S02 (which i now set to a reasonable value),
>>> I am interested in determining N, but it is highly correlated with
>>> sigma2. Each time when disorder in the sample increases, the sigma2
>>> increases and due to its high correlation, N is also overestimated.
>>> On the other hand, when the disorder in the sample decreases, the
>>> sigma2 decreases and I can have a "true" estimation of N in the
>>> sample. Can I still apply the above mentioned approach to break the correlationship between N and sigma2 and get a "true"
>>> estimation of N, even if disorder is high in my samples ? or it is
>>> simply not possible due to the fact that both N and sigma2 varies
>>> with changes inside the sample.
>> N and S02 are always 100% correlated (mathematically, not merely by the finite k range). So, to the extent that the approach works at all, you can use it for "N" or "S02". Really, the approach is comparing N*S02 and sigma2, in one case you asserted a value of "N" and projected all changes to "S02" -- you can equally assert "S02" and project all changes to "N".
>>
>> To be clear, this is not going to find the "true" value of anything, because no analysis is ever going to find the "true" value -- it's going to find a measured value.
>>
>> Finally, the correlation of N*S02 and sigma2 does not imply a bias in the values for N*S02. N*S02 is NOT overestimated because it is highly correlated with sigma2.
>>
>> Hope that helps,
>>
>> --Matt
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1
0
Re: [Ifeffit] Breaking down correlationships between parameters
by Rana, Jatinkumar Kantilal 23 Mar '15
by Rana, Jatinkumar Kantilal 23 Mar '15
23 Mar '15
Hi Scott,
Thanks for your explanation. It means the reverse can also be true, i.e., I can guess N1 (nearest-neighbors in the first shell) and S02 by setting N2, N3 and N4 to values known from other analysis. I did a quick check by fitting the data.
I conducted two fits:
1) setting S02 and guessing only N1
2) guessing both N1 and S02.
To my surprise, both the fits gave very similar results, except that the fit#1 refined value of N1 to a higher side, while fit#2 estimated N1 closer to a physically reasonable value (as expected).
I always constrained S02 when refining N for any path, due to 100% correlation between them. However, I am surprised to know that they can be refined independently.
Best regards,
Jatin
-----Original Message-----
From: ifeffit-bounces(a)millenia.cars.aps.anl.gov [mailto:ifeffit-bounces@millenia.cars.aps.anl.gov] On Behalf Of ifeffit-request(a)millenia.cars.aps.anl.gov
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Today's Topics:
1. Re: Breaking down correlationships between parameters
(Scott Calvin)
----------------------------------------------------------------------
Message: 1
Date: Mon, 23 Mar 2015 09:18:21 -0400
From: Scott Calvin <scalvin(a)sarahlawrence.edu>
To: XAFS Analysis using Ifeffit <ifeffit(a)millenia.cars.aps.anl.gov>
Subject: Re: [Ifeffit] Breaking down correlationships between
parameters
Message-ID: <78C1636C-91CF-4C8C-9D48-3EC361BB7237(a)slc.edu>
Content-Type: text/plain; charset="utf-8"
Hi Jatin,
The key is that S02 should be the same for all paths.
For example:
Suppose you are very confident path 1 has a coordination number of 6, because of prior knowledge you have about the system. Paths 2, 3, and 4 have unknown coordination numbers, however.
N1 (i.e. the degeneracy of path 1) you set to 6.
You guess S02, N2, N3, and N4. Of course, the way Artemis and Ifeffit implement that, you're writing N1*S02 for the S02 field of Path 1, N2*S02 for the S02 field of Path 2, etc., and then setting N1 = 6 and guessing S02, N2, N3, and N4.
There is now enough information for S02, N2, N3, and N4 to each be fitted without 100% correlation.
?Scott Calvin
Sarah Lawrence College
> On Mar 23, 2015, at 8:54 AM, Rana, Jatinkumar Kantilal <jatinkumar.rana(a)helmholtz-berlin.de> wrote:
>
> Hi Chris,
>
> The term N*S02 is fitted for each path of the FEFF calculation. So my question is, even if we know N with a great certainty for some path, how can we vary both N and S02 for other paths ? or Did I understand it wrong ?
>
> Best regards,
> Jatin
>
> -----Original Message-----
> From: ifeffit-bounces(a)millenia.cars.aps.anl.gov
> [mailto:ifeffit-bounces@millenia.cars.aps.anl.gov] On Behalf Of
> ifeffit-request(a)millenia.cars.aps.anl.gov
> Sent: 23 March, 2015 12:16
> To: ifeffit(a)millenia.cars.aps.anl.gov
> Subject: Ifeffit Digest, Vol 145, Issue 42
>
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> Today's Topics:
>
> 1. Re: Breaking down correlationships between parameters
> (Rana, Jatinkumar Kantilal)
> 2. Re: Breaking down correlationships between parameters
> (Chris Patridge)
>
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Mon, 23 Mar 2015 11:00:19 +0000
> From: "Rana, Jatinkumar Kantilal"
> <jatinkumar.rana(a)helmholtz-berlin.de>
> To: "ifeffit(a)millenia.cars.aps.anl.gov"
> <ifeffit(a)millenia.cars.aps.anl.gov>
> Subject: Re: [Ifeffit] Breaking down correlationships between
> parameters
> Message-ID: <DA4C7D90F90BC249A03505C87F2EB8AB230EE777@didag1>
> Content-Type: text/plain; charset="utf-8"
>
> Hi Scott,
>
> Thank you for your comments. Can you please elaborate a little bit more on this "In cases like that, both N for all paths but one and S02 can be fit without 100% correlation."
>
> Best regards,
> Jatin
>
> -----Original Message-----
> From: ifeffit-bounces(a)millenia.cars.aps.anl.gov
> [mailto:ifeffit-bounces@millenia.cars.aps.anl.gov] On Behalf Of
> ifeffit-request(a)millenia.cars.aps.anl.gov
> Sent: 23 March, 2015 10:16
> To: ifeffit(a)millenia.cars.aps.anl.gov
> Subject: Ifeffit Digest, Vol 145, Issue 41
>
> Send Ifeffit mailing list submissions to
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> Today's Topics:
>
> 1. Re: Breaking down correlationships between parameters
> (Scott Calvin)
> 2. Re: Breaking down correlationships between parameters
> (Matt Newville)
> 3. Re: Breaking down correlationships between parameters
> (Rana, Jatinkumar Kantilal)
>
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Sun, 22 Mar 2015 13:44:28 -0400
> From: Scott Calvin <scalvin(a)sarahlawrence.edu>
> To: XAFS Analysis using Ifeffit <ifeffit(a)millenia.cars.aps.anl.gov>
> Subject: Re: [Ifeffit] Breaking down correlationships between
> parameters
> Message-ID: <E0C66911-7AD2-448C-9F64-F03E262D04D7(a)slc.edu>
> Content-Type: text/plain; charset="utf-8"
>
> One side-comment from me:
>
> On Mar 22, 2015, at 12:52 PM, Matt Newville <newville(a)cars.uchicago.edu<mailto:newville@cars.uchicago.edu>> wrote:
>
> N and S02 are always 100% correlated (mathematically, not merely by the finite k range).
>
> Matt is saying that N and S02 are always 100% correlated for a single path. But in some situations you might know N for one path but not others. For example, you might know that the absorbing atom is octahedrally coordinated to oxygen but not be as certain as to next-nearest neighbors, or that there are copper atoms on the corners of a simple cubic lattice with a mixture of atoms at other positions. In cases like that, both N for all paths but one and S02 can be fit without 100% correlation.
>
> The degeneracy of multiple-scattering paths can often be constrained in terms of the coordination numbers for direct-scattering paths, which can further reduce (not ?break?) the correlation.
>
> In terms of the main question, I agree with Matt: I don?t think there?s much point in using the line-crossing technique nowadays; fitting using multiple k-weights simultaneously accomplishes the same thing but is a bit easier to interpret statistically.
>
> ?Scott Calvin
> Sarah Lawrence College
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> ------------------------------
>
> Message: 2
> Date: Sun, 22 Mar 2015 15:56:20 -0500
> From: Matt Newville <newville(a)cars.uchicago.edu>
> To: XAFS Analysis using Ifeffit <ifeffit(a)millenia.cars.aps.anl.gov>
> Subject: Re: [Ifeffit] Breaking down correlationships between
> parameters
> Message-ID:
>
> <CA+7ESbq_s0X3L9rPDDnwAdhx7h6Ptx5-8guCUFTM2OjwkYEerA(a)mail.gmail.com>
> Content-Type: text/plain; charset="utf-8"
>
> On Sun, Mar 22, 2015 at 12:44 PM, Scott Calvin
> <scalvin(a)sarahlawrence.edu>
> wrote:
>
>> One side-comment from me:
>>
>> On Mar 22, 2015, at 12:52 PM, Matt Newville
>> <newville(a)cars.uchicago.edu>
>> wrote:
>>
>> N and S02 are always 100% correlated (mathematically, not merely by
>> the finite k range).
>>
>>
>> Matt is saying that N and S02 are always 100% correlated *for a
>> single path*. But in some situations you might know N for one path
>> but not others. For example, you might know that the absorbing atom
>> is octahedrally coordinated to oxygen but not be as certain as to
>> next-nearest neighbors, or that there are copper atoms on the corners
>> of a simple cubic lattice with a mixture of atoms at other positions.
>> In cases like that, both N for all paths but one and S02 can be fit without 100% correlation.
>>
>>
> Yes, I completely agree with Scott -- this is a good point that I
> neglected. In addition to looking at multiple shells, one might also
> consider using temperature or pressure dependence to separate N*S02 and
> sigma2. Those aren't without assumptions, and still don't remove the
> inherent correlation, but are useful approaches.
>
> The degeneracy of multiple-scattering paths can often be constrained
> in
>> terms of the coordination numbers for direct-scattering paths, which
>> can further reduce (not ?break?) the correlation.
>>
>> In terms of the main question, I agree with Matt: I don?t think
>> there?s much point in using the line-crossing technique nowadays;
>> fitting using multiple k-weights simultaneously accomplishes the same
>> thing but is a bit easier to interpret statistically.
>>
>> ?Scott Calvin
>> Sarah Lawrence College
>>
>> _______________________________________________
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>>
> --Matt
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> ------------------------------
>
> Message: 3
> Date: Mon, 23 Mar 2015 09:16:02 +0000
> From: "Rana, Jatinkumar Kantilal"
> <jatinkumar.rana(a)helmholtz-berlin.de>
> To: "ifeffit(a)millenia.cars.aps.anl.gov"
> <ifeffit(a)millenia.cars.aps.anl.gov>
> Subject: Re: [Ifeffit] Breaking down correlationships between
> parameters
> Message-ID: <DA4C7D90F90BC249A03505C87F2EB8AB230EE755@didag1>
> Content-Type: text/plain; charset="utf-8"
>
> Hi Matt,
>
> Thank you very much for your detailed explanation. As you pointed out that this approach ignores the statistical significance of fits and assumes that all fits are "good" fits. Also, the point that this approach yields a value of the parameter which is only slightly less correlated with the other one, but not completely removes the correlation. It makes it really clear to me that how this approach works and what are the pros and cons.
>
> Well, I myself has never tried this approach of minimizing the correlation between N*S02 and sigma2, but I read a lot about it in the literature. With my limited knowledge about the method, I could not judge this approach, although I had my own doubts.
>
> I truly appreciate your efforts in providing me a deeper insight into this approach.
>
> Best regards,
> Jatin
>
> -----Original Message-----
> From: ifeffit-bounces(a)millenia.cars.aps.anl.gov
> [mailto:ifeffit-bounces@millenia.cars.aps.anl.gov] On Behalf Of
> ifeffit-request(a)millenia.cars.aps.anl.gov
> Sent: 22 March, 2015 18:00
> To: ifeffit(a)millenia.cars.aps.anl.gov
> Subject: Ifeffit Digest, Vol 145, Issue 40
>
> Send Ifeffit mailing list submissions to
> ifeffit(a)millenia.cars.aps.anl.gov
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>
> Today's Topics:
>
> 1. Re: Breaking down correlationships between parameters
> (Matt Newville)
>
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Sun, 22 Mar 2015 11:52:30 -0500
> From: Matt Newville <newville(a)cars.uchicago.edu>
> To: XAFS Analysis using Ifeffit <ifeffit(a)millenia.cars.aps.anl.gov>
> Subject: Re: [Ifeffit] Breaking down correlationships between
> parameters
> Message-ID:
>
> <CA+7ESbqcyQHf9XUh2uhk=Lv09An7E9LXxqDTX-X6kRJHy9PFzw(a)mail.gmail.com>
> Content-Type: text/plain; charset="utf-8"
>
> Hi Jatin,
>
>
> On Sat, Mar 21, 2015 at 10:41 AM, Rana, Jatinkumar Kantilal < jatinkumar.rana(a)helmholtz-berlin.de> wrote:
>
>> Hi Matt,
>>
>> Thanks a lot for your prompt reply. The method I am referring to is
>> not the multiple k-weight fits by constraining N*S02. My apologies
>> for not being clear enough. Let's do it again. I am actually
>> referring to an approach where we take an advantage of a different
>> k-dependence of various parameters to breakdown correlations between
>> them. For example, S02 and sigma2. S02 is k-independent and Sigma2 has k^2 dependence.
>>
>>
> Yes, I am familiar with this approach, and I understand that this is what you are using. What I am saying is that this does not work nearly as well as (sometimes) claimed, and is sort of cheating. It ignores the measures of statistical significance.
>
> In this case, to breakdown correlation between S02 and sigma2,
>
>
> The correlation between N*S02 and sigma2 is inherent to the finite k-range of the EXAFS signal. It cannot be "broken", though it might be reduced.
>
>
>> one can assume a series of S02 values and perform fits using a single
>> k-weight each time (say k-weight 1,2 and 3) and record corresponding
>> sigma2 values.
>
> Let us say for k-weight =1, a series of preset S02 values will result
> in a
>> series of corresponding sigma2 values refined in fits, which can be
>> plotted as a straight line in sigma2 vs. S02 plot.
>
>
> OK, one can fit sigma2 with a series of preset values on N*S02. That's fine. But it does NOT lead to an infinitely thin line of sigma2 vs.
> N*S02. Each sigma2 value on that line has a width, corresponding to its
> uncertainty. In fact, the line you produce nicely demonstrates and
> measures the correlation of N*S02 and sigma2 as the slope of this line.
>
>
>> Similar straight lines can be obtained for fits using k-weight = 2
>> and then 3.
>
> Now, these three lines may intersect at or near some point, which will
>> determine the "true" value of parameters independent of k-weight.
>
>
> The different lines (each with finite thickness) will give a *range of
> values* for N*S02 and sigma2, not a single value.
>
> The biggest problem with this approach is that it ignores the relative goodness-of-fits (let's just assume that is 'chi-square' for the purpose of
> this discussion) for the fits along these lines. Some fits are better
> than others, and this approach completely ignores that fact, and equally importantly ignores the fact that there is a range of values for chi-square
> that are consistent with "good". If you include these values, your
> linear plot will become contours of chi-square as a function of N*S02 and
> sigma2. And, yes, by using different k-weights and k-ranges and so on you
> can get overlapping contour plots which may reduce the correlation a small amount when looked at as an ensemble. And you can find a best set of values for N*S02 and sigma2, but *each* of these will have an uncertainty.
>
> So, you can use this approach to find a good value for N*S02, but it is not breaking the correlation. You can do this by hand. Or you can just do a
> fit with datasets with different k-weights and k-ranges. When you do this
> as a fit, you will see that the correlation is still fairly large.
>
> Also, just to be clear, this is absolutely not a "true" value. It is a measured value. Not at all the same thing.
>
> One can then constrain S02 to a value obtained from the point of
>> intersection of three lines and vary sigma2 in a fit.
>
>
> Well, one can certainly set N*S02 to some value and fit sigma2. As I said earlier, this ignores the correlation of N*S02 and sigma2, but does not remove that correlation.
>
>
>> In this particular case, however, the advantage is, S02 does not
>> depend on changes inside sample and we have very good estimate of its
>> range (say 0.7
>> - 1.0).
>>
>> Now suppose instead of S02 (which i now set to a reasonable value), I
>> am interested in determining N, but it is highly correlated with
>> sigma2. Each time when disorder in the sample increases, the sigma2
>> increases and due to its high correlation, N is also overestimated.
>> On the other hand, when the disorder in the sample decreases, the
>> sigma2 decreases and I can have a "true" estimation of N in the
>> sample. Can I still apply the above mentioned approach to break the correlationship between N and sigma2 and get a "true"
>> estimation of N, even if disorder is high in my samples ? or it is
>> simply not possible due to the fact that both N and sigma2 varies
>> with changes inside the sample.
>>
>>
> N and S02 are always 100% correlated (mathematically, not merely by the finite k range). So, to the extent that the approach works at all, you can use it for "N" or "S02". Really, the approach is comparing N*S02 and sigma2, in one case you asserted a value of "N" and projected all changes to "S02" -- you can equally assert "S02" and project all changes to "N".
>
> To be clear, this is not going to find the "true" value of anything, because no analysis is ever going to find the "true" value -- it's going to find a measured value.
>
> Finally, the correlation of N*S02 and sigma2 does not imply a bias in the values for N*S02. N*S02 is NOT overestimated because it is highly correlated with sigma2.
>
> Hope that helps,
>
> --Matt
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> Helmholtz-Zentrum Berlin f?r Materialien und Energie GmbH
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> Mitglied der Hermann von Helmholtz-Gemeinschaft Deutscher Forschungszentren e.V.
>
> Aufsichtsrat: Vorsitzender Prof. Dr. Dr. h.c. mult. Joachim Treusch,
> stv. Vorsitzende Dr. Beatrix Vierkorn-Rudolph
> Gesch?ftsf?hrung: Prof. Dr. Anke Rita Kaysser-Pyzalla, Thomas
> Frederking
>
> Sitz Berlin, AG Charlottenburg, 89 HRB 5583
>
> Postadresse:
> Hahn-Meitner-Platz 1
> D-14109 Berlin
>
> http://www.helmholtz-berlin.de
>
>
>
> ------------------------------
>
> Message: 2
> Date: Mon, 23 Mar 2015 07:15:05 -0400
> From: Chris Patridge <patridge(a)buffalo.edu>
> To: XAFS Analysis using Ifeffit <ifeffit(a)millenia.cars.aps.anl.gov>
> Subject: Re: [Ifeffit] Breaking down correlationships between
> parameters
> Message-ID: <29942DF9-8043-424E-BDCC-9CA19EB4AC9B(a)buffalo.edu>
> Content-Type: text/plain; charset=utf-8
>
> I think Scott was pointing out that first neighbors may be known with high certainty and therefore you can set this value thereby removing it and slightly reducing the correlations.
>
> Chris
>
> Sent from my iPhone
>
>> On Mar 23, 2015, at 7:00 AM, Rana, Jatinkumar Kantilal <jatinkumar.rana(a)helmholtz-berlin.de> wrote:
>>
>> Hi Scott,
>>
>> Thank you for your comments. Can you please elaborate a little bit more on this "In cases like that, both N for all paths but one and S02 can be fit without 100% correlation."
>>
>> Best regards,
>> Jatin
>>
>> -----Original Message-----
>> From: ifeffit-bounces(a)millenia.cars.aps.anl.gov
>> [mailto:ifeffit-bounces@millenia.cars.aps.anl.gov] On Behalf Of
>> ifeffit-request(a)millenia.cars.aps.anl.gov
>> Sent: 23 March, 2015 10:16
>> To: ifeffit(a)millenia.cars.aps.anl.gov
>> Subject: Ifeffit Digest, Vol 145, Issue 41
>>
>> Send Ifeffit mailing list submissions to
>> ifeffit(a)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
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>>
>> When replying, please edit your Subject line so it is more specific than "Re: Contents of Ifeffit digest..."
>>
>>
>> Today's Topics:
>>
>> 1. Re: Breaking down correlationships between parameters
>> (Scott Calvin)
>> 2. Re: Breaking down correlationships between parameters
>> (Matt Newville)
>> 3. Re: Breaking down correlationships between parameters
>> (Rana, Jatinkumar Kantilal)
>>
>>
>> ---------------------------------------------------------------------
>> -
>>
>> Message: 1
>> Date: Sun, 22 Mar 2015 13:44:28 -0400
>> From: Scott Calvin <scalvin(a)sarahlawrence.edu>
>> To: XAFS Analysis using Ifeffit <ifeffit(a)millenia.cars.aps.anl.gov>
>> Subject: Re: [Ifeffit] Breaking down correlationships between
>> parameters
>> Message-ID: <E0C66911-7AD2-448C-9F64-F03E262D04D7(a)slc.edu>
>> Content-Type: text/plain; charset="utf-8"
>>
>> One side-comment from me:
>>
>> On Mar 22, 2015, at 12:52 PM, Matt Newville <newville(a)cars.uchicago.edu<mailto:newville@cars.uchicago.edu>> wrote:
>>
>> N and S02 are always 100% correlated (mathematically, not merely by the finite k range).
>>
>> Matt is saying that N and S02 are always 100% correlated for a single path. But in some situations you might know N for one path but not others. For example, you might know that the absorbing atom is octahedrally coordinated to oxygen but not be as certain as to next-nearest neighbors, or that there are copper atoms on the corners of a simple cubic lattice with a mixture of atoms at other positions. In cases like that, both N for all paths but one and S02 can be fit without 100% correlation.
>>
>> The degeneracy of multiple-scattering paths can often be constrained in terms of the coordination numbers for direct-scattering paths, which can further reduce (not ?break?) the correlation.
>>
>> In terms of the main question, I agree with Matt: I don?t think there?s much point in using the line-crossing technique nowadays; fitting using multiple k-weights simultaneously accomplishes the same thing but is a bit easier to interpret statistically.
>>
>> ?Scott Calvin
>> Sarah Lawrence College
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>>
>> ------------------------------
>>
>> Message: 2
>> Date: Sun, 22 Mar 2015 15:56:20 -0500
>> From: Matt Newville <newville(a)cars.uchicago.edu>
>> To: XAFS Analysis using Ifeffit <ifeffit(a)millenia.cars.aps.anl.gov>
>> Subject: Re: [Ifeffit] Breaking down correlationships between
>> parameters
>> Message-ID:
>>
>> <CA+7ESbq_s0X3L9rPDDnwAdhx7h6Ptx5-8guCUFTM2OjwkYEerA(a)mail.gmail.com>
>> Content-Type: text/plain; charset="utf-8"
>>
>> On Sun, Mar 22, 2015 at 12:44 PM, Scott Calvin
>> <scalvin(a)sarahlawrence.edu>
>> wrote:
>>
>>> One side-comment from me:
>>>
>>> On Mar 22, 2015, at 12:52 PM, Matt Newville
>>> <newville(a)cars.uchicago.edu>
>>> wrote:
>>>
>>> N and S02 are always 100% correlated (mathematically, not merely by
>>> the finite k range).
>>>
>>>
>>> Matt is saying that N and S02 are always 100% correlated *for a
>>> single path*. But in some situations you might know N for one path
>>> but not others. For example, you might know that the absorbing atom
>>> is octahedrally coordinated to oxygen but not be as certain as to
>>> next-nearest neighbors, or that there are copper atoms on the
>>> corners of a simple cubic lattice with a mixture of atoms at other positions.
>>> In cases like that, both N for all paths but one and S02 can be fit without 100% correlation.
>> Yes, I completely agree with Scott -- this is a good point that I
>> neglected. In addition to looking at multiple shells, one might also
>> consider using temperature or pressure dependence to separate N*S02 and
>> sigma2. Those aren't without assumptions, and still don't remove the
>> inherent correlation, but are useful approaches.
>>
>> The degeneracy of multiple-scattering paths can often be constrained
>> in
>>> terms of the coordination numbers for direct-scattering paths, which
>>> can further reduce (not ?break?) the correlation.
>>>
>>> In terms of the main question, I agree with Matt: I don?t think
>>> there?s much point in using the line-crossing technique nowadays;
>>> fitting using multiple k-weights simultaneously accomplishes the
>>> same thing but is a bit easier to interpret statistically.
>>>
>>> ?Scott Calvin
>>> Sarah Lawrence College
>>>
>>> _______________________________________________
>>> Ifeffit mailing list
>>> Ifeffit(a)millenia.cars.aps.anl.gov
>>> http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
>> --Matt
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>> 3
>> 22/3dd3f763/attachment-0001.htm>
>>
>> ------------------------------
>>
>> Message: 3
>> Date: Mon, 23 Mar 2015 09:16:02 +0000
>> From: "Rana, Jatinkumar Kantilal"
>> <jatinkumar.rana(a)helmholtz-berlin.de>
>> To: "ifeffit(a)millenia.cars.aps.anl.gov"
>> <ifeffit(a)millenia.cars.aps.anl.gov>
>> Subject: Re: [Ifeffit] Breaking down correlationships between
>> parameters
>> Message-ID: <DA4C7D90F90BC249A03505C87F2EB8AB230EE755@didag1>
>> Content-Type: text/plain; charset="utf-8"
>>
>> Hi Matt,
>>
>> Thank you very much for your detailed explanation. As you pointed out that this approach ignores the statistical significance of fits and assumes that all fits are "good" fits. Also, the point that this approach yields a value of the parameter which is only slightly less correlated with the other one, but not completely removes the correlation. It makes it really clear to me that how this approach works and what are the pros and cons.
>>
>> Well, I myself has never tried this approach of minimizing the correlation between N*S02 and sigma2, but I read a lot about it in the literature. With my limited knowledge about the method, I could not judge this approach, although I had my own doubts.
>>
>> I truly appreciate your efforts in providing me a deeper insight into this approach.
>>
>> Best regards,
>> Jatin
>>
>> -----Original Message-----
>> From: ifeffit-bounces(a)millenia.cars.aps.anl.gov
>> [mailto:ifeffit-bounces@millenia.cars.aps.anl.gov] On Behalf Of
>> ifeffit-request(a)millenia.cars.aps.anl.gov
>> Sent: 22 March, 2015 18:00
>> To: ifeffit(a)millenia.cars.aps.anl.gov
>> Subject: Ifeffit Digest, Vol 145, Issue 40
>>
>> Send Ifeffit mailing list submissions to
>> ifeffit(a)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-request(a)millenia.cars.aps.anl.gov
>>
>> You can reach the person managing the list at
>> ifeffit-owner(a)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: Breaking down correlationships between parameters
>> (Matt Newville)
>>
>>
>> ---------------------------------------------------------------------
>> -
>>
>> Message: 1
>> Date: Sun, 22 Mar 2015 11:52:30 -0500
>> From: Matt Newville <newville(a)cars.uchicago.edu>
>> To: XAFS Analysis using Ifeffit <ifeffit(a)millenia.cars.aps.anl.gov>
>> Subject: Re: [Ifeffit] Breaking down correlationships between
>> parameters
>> Message-ID:
>>
>> <CA+7ESbqcyQHf9XUh2uhk=Lv09An7E9LXxqDTX-X6kRJHy9PFzw(a)mail.gmail.com>
>> Content-Type: text/plain; charset="utf-8"
>>
>> Hi Jatin,
>>
>>
>>> On Sat, Mar 21, 2015 at 10:41 AM, Rana, Jatinkumar Kantilal < jatinkumar.rana(a)helmholtz-berlin.de> wrote:
>>>
>>> Hi Matt,
>>>
>>> Thanks a lot for your prompt reply. The method I am referring to is
>>> not the multiple k-weight fits by constraining N*S02. My apologies
>>> for not being clear enough. Let's do it again. I am actually
>>> referring to an approach where we take an advantage of a different
>>> k-dependence of various parameters to breakdown correlations between
>>> them. For example, S02 and sigma2. S02 is k-independent and Sigma2 has k^2 dependence.
>> Yes, I am familiar with this approach, and I understand that this is what you are using. What I am saying is that this does not work nearly as well as (sometimes) claimed, and is sort of cheating. It ignores the measures of statistical significance.
>>
>> In this case, to breakdown correlation between S02 and sigma2,
>>
>>
>> The correlation between N*S02 and sigma2 is inherent to the finite k-range of the EXAFS signal. It cannot be "broken", though it might be reduced.
>>
>>
>>> one can assume a series of S02 values and perform fits using a
>>> single k-weight each time (say k-weight 1,2 and 3) and record
>>> corresponding
>>> sigma2 values.
>>
>> Let us say for k-weight =1, a series of preset S02 values will result
>> in a
>>> series of corresponding sigma2 values refined in fits, which can be
>>> plotted as a straight line in sigma2 vs. S02 plot.
>>
>>
>> OK, one can fit sigma2 with a series of preset values on N*S02. That's fine. But it does NOT lead to an infinitely thin line of sigma2 vs.
>> N*S02. Each sigma2 value on that line has a width, corresponding to its
>> uncertainty. In fact, the line you produce nicely demonstrates and
>> measures the correlation of N*S02 and sigma2 as the slope of this line.
>>
>>
>>> Similar straight lines can be obtained for fits using k-weight = 2
>>> and then 3.
>>
>> Now, these three lines may intersect at or near some point, which
>> will
>>> determine the "true" value of parameters independent of k-weight.
>>
>>
>> The different lines (each with finite thickness) will give a *range
>> of
>> values* for N*S02 and sigma2, not a single value.
>>
>> The biggest problem with this approach is that it ignores the relative goodness-of-fits (let's just assume that is 'chi-square' for the purpose of
>> this discussion) for the fits along these lines. Some fits are better
>> than others, and this approach completely ignores that fact, and equally importantly ignores the fact that there is a range of values for chi-square
>> that are consistent with "good". If you include these values, your
>> linear plot will become contours of chi-square as a function of N*S02 and
>> sigma2. And, yes, by using different k-weights and k-ranges and so on you
>> can get overlapping contour plots which may reduce the correlation a small amount when looked at as an ensemble. And you can find a best set of values for N*S02 and sigma2, but *each* of these will have an uncertainty.
>>
>> So, you can use this approach to find a good value for N*S02, but it is not breaking the correlation. You can do this by hand. Or you can just do a
>> fit with datasets with different k-weights and k-ranges. When you do this
>> as a fit, you will see that the correlation is still fairly large.
>>
>> Also, just to be clear, this is absolutely not a "true" value. It is a measured value. Not at all the same thing.
>>
>> One can then constrain S02 to a value obtained from the point of
>>> intersection of three lines and vary sigma2 in a fit.
>>
>>
>> Well, one can certainly set N*S02 to some value and fit sigma2. As I said earlier, this ignores the correlation of N*S02 and sigma2, but does not remove that correlation.
>>
>>
>>> In this particular case, however, the advantage is, S02 does not
>>> depend on changes inside sample and we have very good estimate of
>>> its range (say 0.7
>>> - 1.0).
>>>
>>> Now suppose instead of S02 (which i now set to a reasonable value),
>>> I am interested in determining N, but it is highly correlated with
>>> sigma2. Each time when disorder in the sample increases, the sigma2
>>> increases and due to its high correlation, N is also overestimated.
>>> On the other hand, when the disorder in the sample decreases, the
>>> sigma2 decreases and I can have a "true" estimation of N in the
>>> sample. Can I still apply the above mentioned approach to break the correlationship between N and sigma2 and get a "true"
>>> estimation of N, even if disorder is high in my samples ? or it is
>>> simply not possible due to the fact that both N and sigma2 varies
>>> with changes inside the sample.
>> N and S02 are always 100% correlated (mathematically, not merely by the finite k range). So, to the extent that the approach works at all, you can use it for "N" or "S02". Really, the approach is comparing N*S02 and sigma2, in one case you asserted a value of "N" and projected all changes to "S02" -- you can equally assert "S02" and project all changes to "N".
>>
>> To be clear, this is not going to find the "true" value of anything, because no analysis is ever going to find the "true" value -- it's going to find a measured value.
>>
>> Finally, the correlation of N*S02 and sigma2 does not imply a bias in the values for N*S02. N*S02 is NOT overestimated because it is highly correlated with sigma2.
>>
>> Hope that helps,
>>
>> --Matt
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>> ________________________________
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>> Helmholtz-Zentrum Berlin f?r Materialien und Energie GmbH
>>
>> Mitglied der Hermann von Helmholtz-Gemeinschaft Deutscher Forschungszentren e.V.
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>> Gesch?ftsf?hrung: Prof. Dr. Anke Rita Kaysser-Pyzalla, Thomas
>> Frederking
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>> Sitz Berlin, AG Charlottenburg, 89 HRB 5583
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>>
>> ________________________________
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>>
>> Mitglied der Hermann von Helmholtz-Gemeinschaft Deutscher Forschungszentren e.V.
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>> stv. Vorsitzende Dr. Beatrix Vierkorn-Rudolph
>> Gesch?ftsf?hrung: Prof. Dr. Anke Rita Kaysser-Pyzalla, Thomas
>> Frederking
>>
>> Sitz Berlin, AG Charlottenburg, 89 HRB 5583
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1
0
Re: [Ifeffit] Breaking down correlationships between parameters
by Rana, Jatinkumar Kantilal 23 Mar '15
by Rana, Jatinkumar Kantilal 23 Mar '15
23 Mar '15
Hi Chris,
The term N*S02 is fitted for each path of the FEFF calculation. So my question is, even if we know N with a great certainty for some path, how can we vary both N and S02 for other paths ? or Did I understand it wrong ?
Best regards,
Jatin
-----Original Message-----
From: ifeffit-bounces(a)millenia.cars.aps.anl.gov [mailto:ifeffit-bounces@millenia.cars.aps.anl.gov] On Behalf Of ifeffit-request(a)millenia.cars.aps.anl.gov
Sent: 23 March, 2015 12:16
To: ifeffit(a)millenia.cars.aps.anl.gov
Subject: Ifeffit Digest, Vol 145, Issue 42
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Today's Topics:
1. Re: Breaking down correlationships between parameters
(Rana, Jatinkumar Kantilal)
2. Re: Breaking down correlationships between parameters
(Chris Patridge)
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Message: 1
Date: Mon, 23 Mar 2015 11:00:19 +0000
From: "Rana, Jatinkumar Kantilal"
<jatinkumar.rana(a)helmholtz-berlin.de>
To: "ifeffit(a)millenia.cars.aps.anl.gov"
<ifeffit(a)millenia.cars.aps.anl.gov>
Subject: Re: [Ifeffit] Breaking down correlationships between
parameters
Message-ID: <DA4C7D90F90BC249A03505C87F2EB8AB230EE777@didag1>
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Hi Scott,
Thank you for your comments. Can you please elaborate a little bit more on this "In cases like that, both N for all paths but one and S02 can be fit without 100% correlation."
Best regards,
Jatin
-----Original Message-----
From: ifeffit-bounces(a)millenia.cars.aps.anl.gov [mailto:ifeffit-bounces@millenia.cars.aps.anl.gov] On Behalf Of ifeffit-request(a)millenia.cars.aps.anl.gov
Sent: 23 March, 2015 10:16
To: ifeffit(a)millenia.cars.aps.anl.gov
Subject: Ifeffit Digest, Vol 145, Issue 41
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Today's Topics:
1. Re: Breaking down correlationships between parameters
(Scott Calvin)
2. Re: Breaking down correlationships between parameters
(Matt Newville)
3. Re: Breaking down correlationships between parameters
(Rana, Jatinkumar Kantilal)
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Message: 1
Date: Sun, 22 Mar 2015 13:44:28 -0400
From: Scott Calvin <scalvin(a)sarahlawrence.edu>
To: XAFS Analysis using Ifeffit <ifeffit(a)millenia.cars.aps.anl.gov>
Subject: Re: [Ifeffit] Breaking down correlationships between
parameters
Message-ID: <E0C66911-7AD2-448C-9F64-F03E262D04D7(a)slc.edu>
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One side-comment from me:
On Mar 22, 2015, at 12:52 PM, Matt Newville <newville(a)cars.uchicago.edu<mailto:newville@cars.uchicago.edu>> wrote:
N and S02 are always 100% correlated (mathematically, not merely by the finite k range).
Matt is saying that N and S02 are always 100% correlated for a single path. But in some situations you might know N for one path but not others. For example, you might know that the absorbing atom is octahedrally coordinated to oxygen but not be as certain as to next-nearest neighbors, or that there are copper atoms on the corners of a simple cubic lattice with a mixture of atoms at other positions. In cases like that, both N for all paths but one and S02 can be fit without 100% correlation.
The degeneracy of multiple-scattering paths can often be constrained in terms of the coordination numbers for direct-scattering paths, which can further reduce (not ?break?) the correlation.
In terms of the main question, I agree with Matt: I don?t think there?s much point in using the line-crossing technique nowadays; fitting using multiple k-weights simultaneously accomplishes the same thing but is a bit easier to interpret statistically.
?Scott Calvin
Sarah Lawrence College
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