Hi,

These match the parameters as listed in the help for the
model_free.select_model() user function.  The grid search arrays match
the parameter arrays.

Regards,

Edward


On 6 April 2011 18:54, Tiago Pais <[email protected]> wrote:
> Ok,
> Im sorry to insist but I am probably missing something here. How do I state
> which bound goes with which parameter? That is, which position in the array
> bound corresponds to the S2f parameter?
> Regards.
> TP
>
> -----Original Message-----
> From: [email protected] [mailto:[email protected]] On
> Behalf Of Edward d'Auvergne
> Sent: quarta-feira, 6 de Abril de 2011 17:42
> To: Tiago Pais
> Cc: [email protected]
> Subject: Re: How to set S2f to 0.111?
>
> Hi,
>
> That is roughly correct.  Just set the lower and upper bound to 0.111
> and set the number of increments for that parameter to 1.  Then it is
> like a grid search without S2f being present, or being fixed to 0.111.
>
> Regards,
>
> Edward
>
>
>
> On 6 April 2011 18:38, Tiago Pais <[email protected]> wrote:
>> Hi Ed,
>> Thanks for the quick reply.
>> Let's see if I understand your suggestion. For example, the
> mf_multimodel.py
>> sample script performs a grid search minimization using the grid_search
>> function. So if I insert an array of upper and lower bounds for the
>> parameters in the model I can constrain the interval of possible results,
>> correct? If so, what is the sequence for the parameters in the array?
>> TP
>>
>>
>>
>> -----Original Message-----
>> From: Edward d'Auvergne [mailto:[email protected]]
>> Sent: quarta-feira, 6 de Abril de 2011 17:13
>> To: Tiago Pais
>> Cc: [email protected]
>> Subject: Re: How to set S2f to 0.111?
>>
>> Hi,
>>
>> Unfortunately, there is no ability to fix one of the model-free
>> parameters during optimisation in relax yet.  This is something that
>> has been requested one or two times over the years.  This is
>> complicated as the gradients and Hessians (first and second partial
>> derivates) need to be modified with this in mind, as the curvature of
>> the space changes.  The fixed parameter is not part of the gradient or
>> Hessian, and has to be removed.  This really complicates the target
>> function, gradient, and Hessian and, due to the low demand, has not
>> been implemented.
>>
>> Are you able to optimise this parameter and see if you get 0.111?  And
>> are you able to extract the timescale of this process (the methyl
>> group rotamer jumps)?  From memory, someone has optimsed these models
>> using a grid search.  This coarse optimisation can be performed in
>> relax as you are able to specify the fine details of the grid search.
>> It is slower, but will do the job.  You could even implement a zooming
>> grid search if your scripting skills are up to it to be able to
>> relatively quickly find the parameters to high precision.  Anyway, I
>> hope this info helps.
>>
>> Regards,
>>
>> Edward
>>
>>
>>
>>
>>
>> On 6 April 2011 17:39, Tiago Pais <[email protected]> wrote:
>>> Hi,
>>>
>>> I would like to make an analysis of side-chain relaxation data with the
>> S2f
>>> parameter (in model 5) set to 0.111.
>>>
>>> Is it possible to do this with RELAX? How?
>>>
>>> Thanks in advance.
>>>
>>> Cheers
>>>
>>> Tiago P
>>>
>>>
>>>
>>> **************************************
>>>
>>> Tiago Pais, PhD. student
>>>
>>> Cell Physiology & NMR
>>>
>>> Instituto de Tecnologia Química e Biológica-Oeiras
>>>
>>>
>>>
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