[cctbxbb] constrained hydrogen geometry
Luc Bourhis
luc_j_bourhis at mac.com
Thu Dec 14 14:31:07 PST 2006
>> I manage to find how position and ADP constraints are handled
>> by constraint objects featuring methods to return the independent
>> variables and the gradient with respect to them. Then cctbx/cctbx/
>> examples/structure_factor_derivatives_4.py shows how those features
>> can be used. Would Hydrogen geometry constraint be best handled by
>> mimicking those special positions constraint?
>
> I am not sure. The handling of hydrogens seems more complicated than
> dealing with the constraints due to symmetry. I just had a quick look
> at the SHELX manual. I see many special cases.
Aplenty indeed. Right. Let me precise my question then. The two
classes dealing with position and ADP symmetry constraints feature
the same methods:
- n_independent_params
- independent_params
- all_params
- independent_gradients
- independent_curvatures
- gradient_sum_matrix
I was trying to figure out whether this interface would be sufficient
and/or necessary for the Hydrogen geometry constraints. I am not
quite sure I understand what is gradient_sum_matrix exactly in fact.
> If I had a chance to work on this, I'd start with a Python script
> emulating some of the cases handled by SHELX, refining a few small
> structures. After getting a few concrete examples to work, I'd try to
> generalize the procedures for handling the special cases. I'd
> switch to
> C++ only after having fully conquered the math and the bookkeeping in
> Python, and being sure about the final interfaces.
It is the philosophy of the cctbx, isn't it? You have constructed the
cctbx so as to use it as Python library, relegating C++ to some sort
of assembly language for efficiency. The lack of abstraction in the C+
+ code of the cctbx (hardly any inheritance, no advanced genericity)
would require wrapping a lot of the cctbx classes behind proxies
inheriting from abstract types. A typical example for me are those
classes dealing with position constraints and ADP constraints. They
are unrelated in C++, cctbx::sgtbx::site_constraints and
cctbx::sgtbx::tensor_rank_2::constraints, although they have both
have the same member functions listed above. Of course, from Python,
it does not matter, thanks to duck typing: if two objects answer the
same method calls, then they are by all practical means of the same
type.
> To implement the core refinement, I'd copy and modify
> cctbx/cctbx/xray/minimization.py. See also
> phenix/phenix/substructure/hyss/minimization.py, which you can find
> in the CCI Apps bundle (http://phenix-online.org/download/cci_apps/).
I have already started to study the former. Thanks for pointing out
the latter.
> Hope this helps. As you can tell, I am not an expert in constrained
> hydrogen refinement, but I'm very interested in seeing such algorithms
> in the cctbx (we'd probably want to use them in phenix.refine). Let me
> know if you feel I can do something to help out.
Our group would be more than happy to contribute them to the cctbx
since we absolutely need them for our project.
Cheerio,
Luc
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