[cctbxbb] constrained hydrogen geometry

[Luc Bourhis]

>>  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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