Please see this attachment. Thank you so much.
Dien
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1. Re: [EXTERNAL] Ifeffit Digest, Vol 235, Issue 10
(Dien.Li@srnl.doe.gov)
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Date: Thu, 15 Sep 2022 17:41:19 +0000
From: "Dien.Li@srnl.doe.gov"
To: "ifeffit@millenia.cars.aps.anl.gov"
Subject: Re: [Ifeffit] [EXTERNAL] Ifeffit Digest, Vol 235, Issue 10
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Hi, Matt and EXAFS experts
Thank you so much. Our sample is porous silica + PO4 ligand on surface/pore, then react with LaNO3 in solution. The model is that La is bonding with PO4 through both mono- (corner-sharing) and di-dentate (edge sharing) modes.
Please see the attachment. The first three fits in history are fits with increasing paths, with fixed CN for the La-P11 and La-P14 path, the ss parameters are reasonable, but to fix CN at 3 for La-P14 is unreasonable, which requires La to bind with three different PO4 groups.
The last three fits are fits with increasing paths, in which CN was fitted, the fitted parameters are reasonable, EXCEPT for the negative ss parameters for the path La-P11 (edge sharing) and La-P14 (corner sharing). By the way, the length for La-P14 is +0.3 A, it is large, but not completely unreasonable, because the bond distances of La-O polyhedron may change from 2.4 to 3.1 A.
Is it possible to constrain ss parameter? If so, how to set up this constrain? Thank you so much for your further instruction.
Dien
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Today's Topics:
1. Re: Larch: Fitting error of the objective/model function
(Matt Newville)
2. Re: Help for EXAFS fitting (Matt Newville)
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Message: 1
Date: Wed, 14 Sep 2022 13:28:38 -0500
From: Matt Newville
To: XAFS Analysis using Ifeffit
Subject: Re: [Ifeffit] Larch: Fitting error of the objective/model
function
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Hi Fan,
Sorry for the trouble. That seems like a strange error to me - I don't see
why changing those expressions for E0s (even if they are "slightly
complicated"!) should generate NaNs or Infinities. I don't think I've seen
that happen with "feffit" fittings. Can you send me a Larch Session File
with this fit in it?
One suggestion is to place bounds (say +/- 20 eV) on those Parameters, say
pars.del_e0_11=param(expr='0.5*del_e0_O+0.5*del_e0_Sr', min=-20, max=20)
But I'm not certain whether that would solve this problem.
On Wed, Sep 14, 2022 at 7:53 AM wrote:
Dear All
I am doing Temperature-dependent EXAFS experiment with a lot of data.
Usually, we do these kinds of data fitting by several steps, like below:
First, put every parameter free, and obtain the averaged value of amp.
Second, set the amp to the averaged value, put other parameters free, and
then obtain the averaged value of del_e0.
Third, set the amp and del_e0 to the averaged value, and fit again.
In my case, my sample is perovskite structure (Ti K-edge of SrTiO3).
To increase the fitting accuracy, I use three del_e0 for O, Ti, Sr as
suggested in paper: Haskel, D., et al. Physica B: Condensed Matter 208
(1995): 151-153.
The fitting parameters of Cubic model is this:
setattr(pars, f'alpha', param(0, vary=True))
setattr(pars, f'amp', param(0, vary=True))
setattr(pars, f'del_e0_O', param(0, vary=True))
setattr(pars, f'del_e0_Sr', param(0, vary=True))
setattr(pars, f'del_e0_Ti', param(0, vary=True))
setattr(pars, f'sig2_O', param(.002, vary=True))
setattr(pars, f'sig2_Sr', param(.002, vary=True))
setattr(pars, f'sig2_Ti', param(.002, vary=True))
setattr(pars, f'sig2_Tr1', param(.002, vary=True))
setattr(pars, f'sig2_p', param(.002, vary=True))
setattr(pars, f'sig2_Tr2', param(.002, vary=True))
#del_e0 for each path
pars.del_e0_1=param(expr='del_e0_O')
pars.del_e0_2=param(expr='del_e0_O')
pars.del_e0_3=param(expr='del_e0_Sr')
pars.del_e0_4=param(expr='del_e0_Ti')
pars.del_e0_5=param(expr='del_e0_O')
pars.del_e0_6=param(expr='0.5*del_e0_O+0.5*del_e0_Ti')
pars.del_e0_7=param(expr='(2*del_e0_O+del_e0_Ti)/3')
pars.del_e0_8=param(expr='(2*del_e0_O+del_e0_Ti)/3')
pars.del_e0_9=param(expr='(2*del_e0_O+del_e0_Ti)/3')
pars.del_e0_10=param(expr='(2*del_e0_O+del_e0_Ti)/3')
pars.del_e0_11=param(expr='0.5*del_e0_O+0.5*del_e0_Sr')
In the first step, the fitting is fine, I obtained the averaged amp.
However, in the second step, when I set amp to the averaged value, Error
happens for ?some? of the data.
When I use different averaged amp value, the data that happens error is
different.
The error is:
Traceback (most recent call last):
File "STO16_C_2.py", line 250, in <module>
out = feffit(pars, dset)
File
"D:\anaconda3\envs\xraylarch\lib\site-packages\larch\xafs\feffit.py", line
557, in feffit
result = fit.leastsq()
File "D:\anaconda3\envs\xraylarch\lib\site-packages\lmfit\minimizer.py",
line 1689, in leastsq
lsout = scipy_leastsq(self.__residual, variables, **lskws)
File
"D:\anaconda3\envs\xraylarch\lib\site-packages\scipy\optimize\minpack.py",
line 423, in leastsq
retval = _minpack._lmdif(func, x0, args, full_output, ftol, xtol,
File "D:\anaconda3\envs\xraylarch\lib\site-packages\lmfit\minimizer.py",
line 601, in __residual
return _nan_policy(np.asarray(out).ravel(),
File "D:\anaconda3\envs\xraylarch\lib\site-packages\lmfit\minimizer.py",
line 2436, in _nan_policy
raise ValueError(msg)
ValueError: NaN values detected in your input data or the output of your
objective/model function - fitting algorithms cannot handle this! Please
read
https://lmfit.github.io/lmfit-py/faq.html#i-get-errors-from-nan-in-my-fit-wh...
for more information.
I don?t know what happened, can somebody help me figure this out?
PS: when I use only one del_e0 for every path, no such error happens.
Best regards
Fan
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