Hi,
relax already stores all the bond vectors in the spin container, if
the ave argument to structure.vectors() is set to False and multiple
models are loaded. There's nothing to dump these values to a file yet
though (value.write() I don't think can output lists or vectors), or
nothing to really process these vectors. A script skeleton that could
access all these vectors though would be something like:
from generic_fns.mol_res_spin import spin_loop
pipe.create()
structure.read_pdb()
structure.vectors()
for spin in spin_loop():
print spin.xh_vect
This gives you access to the data you require - you just have to set
up the arguments correctly and dump the data as you wish.
Regards,
Edward
On Sat, Jan 17, 2009 at 10:33 PM, Sébastien Morin
<sebastien.mori...@ulaval.ca> wrote:
> Hi Ed,
>
> Thanks for the detailed and rapid answer !
>
> These functionalities would be great ! The use of X-H vectors
> orientations spread could be used in cases where several structures are
> present to assess flexibility from different structures ! This would
> allow a better use of these structures, but also a better
> rationalization of NMR dynamics !
>
> I propose these ideas could be added in the (already quite long) todo
> list... ;)
>
> As for what will soon be possible within relax, i.e. the possibility for
> the spin container to be filled with a list of orientations, how would
> you use relax to extract these orientations and output a list for each
> spin ? Is there a sample script for doing something like that ? This
> would be useful for someone interested in getting the orientations and
> analysing them out of relax, until the code is present... ;)
>
> Regards,
>
>
> Séb :)
>
>
>
>
> Edward d'Auvergne wrote:
>> Hi,
>>
>> I'm actually changing that code at the moment. If you follow my
>> commit messages you'll see how this will be handled in relax, very
>> soon. The changes are happening in the multi_structure branch where I
>> am introducing the distinction between different models (the same
>> molecules but with different conformations) verses different molecules
>> within one model. I'm modifying the structure.vectors() user function
>> now, and this is probably the one you are interested in. Using this
>> function, you can extract the vectors from all different models and
>> these will be placed in the spin container. With the 'ave' arg set to
>> False, each spin container will have a list of 3D vectors for all
>> models.
>>
>> As for analysing the spread of these vectors and then doing something
>> with that, nothing is present in relax. If you would like to have
>> this functionality, a little work will need to be done and a few
>> algorithms designed. The eliminate() user function for deselecting
>> spins is close but not quite what you need. It accepts an arbitrary
>> function but is not the correct place for this idea. Better would be
>> something like:
>>
>> deselect.mobile()
>> deselect.structural_noise()
>> deselect.vectors()
>> deselect.spread_vectors()
>>
>> with an argument such as (vector_spread_cutoff=0.53), where 0.53 is
>> some measure of the spread. This might be expandable to B-factors.
>> If the name deselect.mobile() is used, this could cover a vector
>> spread, B-factors, low S2 values, etc. Oh, with the deselect user
>> functions, there should always be a counterpart in the select user
>> function class. This will allow the deselected spins of the first
>> analysis to be used in a second with local tm values rather than a
>> global diffusion tensor. Is this what you had in mind?
>>
>> Regards,
>>
>> Edward
>>
>>
>> On Thu, Jan 15, 2009 at 4:33 PM, Sébastien Morin
>> <sebastien.mori...@ulaval.ca> wrote:
>>
>>> Hi,
>>>
>>> We are currently studying a system for which many structures are available.
>>>
>>> We thought it would be a great idea to compare X-H (N-H in our case)
>>> orientations to spot residues for which the orientation varies in the
>>> different structures, i.e. for which there might be important motions.
>>>
>>> We thought this could be useful to eliminate such residues with
>>> tremendous motions from diffusion tensor optimization and test them as
>>> diffusing independently (local tm).
>>>
>>> Is there a way to do that in relax ?
>>>
>>> We saw the sample script 'xh_vector_dist.py' which allows one to plot
>>> the vector orientations distribution. However, what we would like to get
>>> would be a file containing the orientations which could allow us to
>>> compare different structures quantitatively on a per residue basis...
>>>
>>> Thanks for help !
>>>
>>>
>>> Sébastien Morin
>>>
>>> _______________________________________________
>>> relax (http://nmr-relax.com)
>>>
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>>
>>
>
>
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