[Ifeffit] restraints in larch

Sun Oct 7 16:53:52 CDT 2018

Hi Matt and Hanyu

Thanks - the latest version of larch runs wrt
ntot1 = param(expr='nO1+nO2', min=5.0, max=8.5, vary=True)

However, still getting odd gofs/errors:
[[Statistics]]
   nvarys, npts       = 6, 390
   n_independent      = 11.186
   chi_square         = 0.00080359
   reduced chi_square = 0.000154956
   r-factor           = 0.01850
   Akaike info crit   = -94.7257
   Bayesian info crit = -92.2378
....

  delrO1         =  0.132140 +/- unknown   (init=  0.150000)
   delrO2         = -0.446980 +/- unknown   (init= -0.500000)
   enot           = -4.125159 +/- unknown   (init=  0.000000)
   nO1            =  7.000000 +/- unknown   (init=  7.000000)
   nO2            =  0.929177 +/- unknown   (init=  1.000000)
   ntot1          =  7.929177 +/- unknown  = 'nO1+nO2'
   ssO1           =  0.006499 +/- unknown   (init=  0.003000)
 .....
(Please ignore the large init value.)

Running on a Mac 10.13.3.
Happy to send the script & output.
Thanks
Barb.

On Fri, 5 Oct 2018 at 23:02, Matt Newville <newville at cars.uchicago.edu>
wrote:

> Hi Hanyu, Barbara,
>
>
> On Fri, Oct 5, 2018 at 12:55 AM Hanyu Zhang <hxz269 at case.edu> wrote:
>
>> Hi,
>>
>> Thought I'd give my two cents before the experts chime in... I'm only a
>> grad student right now though so make what you want out of it. I also
>> haven't touched Larch for a while now since I got my xafs (Larch) functions
>> working in python several months ago.
>>
>> First off though, ntot1 = param(expr='nO1+nO2', min=5.0, max=8.5) ran
>> without throwing an error in Larch for me... (See screenshot near the
>> middle of this email) So I don't think anyone can really help without more
>> details, but I want to comment on some things:
>>
>>    1. The first thing is that you're missing a vary = True in the
>>    statement for ntot1. Since the default value for vary is False according
>>    to the website, I would add that in if you actually wanted it to be fitted
>>    for during the fitting process (
>>    https://xraypy.github.io/xraylarch/fitting/parameters.html).
>>    2. In addition, when you run ntot1 = param(expr='nO1+nO2', min=5.0,
>>    max=8.5), are nO1 and nO2 pre-defined? If not the computer's not
>>    going to know what to make of those variables.
>>    3. I'd recommend something along the lines of:
>>
>> nO1 = param(7.0, min=5, max=7, vary=True)
>> nO2 = param(1, vary=True),
>> ntot1 = param(expr='nO1+nO2', min=5.0, max=8.5, vary=True)
>>
>> I just tested this on my machine and it didn't throw any errors. (Though
>> it also didn't throw any errors without the 2 fixes I recommended...):
>>
>> [image: Screen Shot 2018-10-05 at 12.55.59 AM.png]
>>
>> I didn't think to check when I took that screenshot but with that line,
>> the vary is in fact set to false:
>>
>> larch> ntot1.vary
>>
>> False
>>
>>
>> In terms of the errors on error calculation --
>>
>>    1. What's the reduced chi-sq? What do you mean by very small? In
>>    physics you want that to be as close to one as possible. Though in xafs the
>>    reduced chi-sq apparently is typically around 100-1000 so I'm confused as
>>    to what you mean by "small". Also, if you're having issues with errorbars
>>    to begin with, I wouldn't trust the chi-sq since that calculation
>>    relies on how big the errorbars are. If the errors are NAN, who knows
>>    what the computer would do to divide those numbers...
>>    2. What do you mean by "errors are not reported"? After the fit, it's
>>    returned in feffit.residual, or something along those lines (
>>    http://cars9.uchicago.edu/xraylarch/fitting/results.html#fitting-results-sec)...
>>    I haven't actually used this myself, so I can't say more.
>>    3. *(Just a comment...)* I don't know if this would help but my
>>    physics professor didn't let me trust the reduced chi-sq and gof
>>    values I was getting until I found out how the errors were calculated. By
>>    default, the errors are calculated by assuming that the noise is white in
>>    R-space and that there's no signal at high-R, so the "signal" near your
>>    rmax is the noise. (
>>    http://cars9.uchicago.edu/xraylarch/xafs/utilities.html#_xafs.estimate_noise,
>>    second to last paragraph)
>>
>>
>> Hope this was at least somewhat helpful,
>> ----------
>> Hanyu (Alice) Zhang
>> *Master's in Materials science | 2019*
>>
>> Research in utilizing XAFS to match current theory of metallic glasses
>> to experimental data
>>
>> *Academic achievements:*
>>
>> *MASMC
>> <https://en.wikipedia.org/wiki/Missouri_Academy_of_Science,_Mathematics_and_Computing>/NWMSU
>> <https://www.nwmissouri.edu/>:* Associate of Science, 2014
>> *CWRU <http://case.edu/>:* Bachelor's of Science in Engineering Physics
>> <http://physics.case.edu/undergraduate-programs/undergrad-degree-programs/bsdegree-engrphys/>
>> , 2018
>> *Honors societies*: National Society of Collegiate Scholars | Tau Beta Pi
>> <http://www.tbp.org> | Pi Mu Epsilon <http://pme-math.org/>
>>
>> *Other interests:*
>>
>> *Clubs*: Case Origami Circle | Case Rocket Team
>> <http://caserocketteam.org> | CWRUbotix <http://cwrubotix.case.edu/> | Case
>> Physics and Astronomy club | Math club
>> *YouTube*: Chinese Operations Lead, Veritasium <http://veritasium.com> (5M
>> subscribers) | Saturday Vlogs <http://bit.ly/AliceZhang>
>>
>>
>>
>> On Thu, Oct 4, 2018 at 8:04 PM Barbara Etschmann <
>> barbara.etschmann at monash.edu> wrote:
>>
>>> Hello
>>>
>>> I'm trying to use larch to refine the coordination of Y in solution. I
>>> need to use 2xO paths to fit the first shell and would like to restrain the
>>> total coordination to be between 5.5 and 8.
>>>
>>> I can apply the constraint to each nO, but not the total, i.e.
>>> nO1 = param(7.0, min=5, max=7, vary=True),
>>> nO2 = param(1, vary=True),
>>>  but
>>> ntot1 = param(expr='nO1+nO2', min=5.0, max=8.5)
>>> does not work.
>>> How can I restrain the total coordination?
>>>
>>>
> I think that should work.  But I can also believe it doesn't ;).   It may
> require a recent version of Larch (0.39 or 0.40 and really lmfit).   I'll
> try to verify that over the next couple of days.
>
>
> Also, having some problems with the gofs and errors - the chi square is
>>> rather small and often the errors are not reported and it is not clear why.
>>>
>>
>
> Hm, not sure. Can you post an example?
> Cheers,
>
> --Matt
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