Hi Pavel,

Thank you for your answer and hints. Trying to just test and understand how the libraries works, this is as far as I have come:

import iotbx.pdb

import mmtbx.model

import mmtbx.f_model

from iotbx import reflection_file_reader

pdb_file = '1gwd.pdb'

mtz_file = '1gwd.mtz'

pdb_inp = iotbx.pdb.input(file_name=pdb_file)

model = mmtbx.model.manager(model_input=pdb_inp)

miller_arrays = reflection_file_reader.any_reflection_file(file_name=mtz_file).as_miller_arrays()

f_obs = miller_arrays[1]

fmodel = mmtbx.f_model.manager(f_obs=f_obs, xray_structure=model.get_xray_structure(), target_name='ls_wunit_k1')

gradients = fmodel.one_time_gradients_wrt_atomic_parameters()

print(list(gradients.d_target_d_site_cart()))

>>> [(0.0, 0.0, 0.0), (0.0, 0.0, 0.0), (0.0, 0.0, 0.0), (0.0, 0.0, 0.0), (0.0, 0.0, 0.0), (0.0, 0.0, 0.0), (0.0, 0.0, 0.0), (0.0, 0.0, 0.0), (0.0, 0.0, 0.0), (0.0, 0.0, 0.0), (0.0, 0.0, 0.0), (0.0, 0.0, 0.0), (0.0, 0.0, 0.0), (0.0, 0.0, 0.0), (0.0, 0.0, 0.0), (0.0, 0.0, 0.0), (0.0, 0.0, 0.0), (0.0, 0.0, 0.0), (0.0, 0.0, 0.0), (0.0, 0.0, 0.0), (0.0, 0.0, 0.0), (0.0, 0.0, 0.0), (0.0, 0.0, 0.0), (0.0, 0.0, 0.0), (0.0, 0.0, 0.0), […]

I would expect the gradients to not be zero for all scatterers so obviously I am doing something wrong – help on how to get further would be very much appreciated.

Best regards

Kristoffer

From: Pavel Afonine <[email protected]>
Date: Friday, 6 October 2023 at 02:35
To: cctbx mailing list <[email protected]>, Kristoffer Lundgren <[email protected]>
Subject: Re: [cctbxbb] Experimental gradients

Hi Kristoffer,

CCTBX is a source of building blocks for Phenix, and Phenix has real- and reciprocal-space refinement programs, phenix.real_space_refine and phenix.refine, so the answer to your question is yes.

You have not specified, but I'm assuming you are looking for gradients of reciprocal space refinement target (LS, ML, MLHL, etc) and real-space target (we have only one described here: https://pubmed.ncbi.nlm.nih.gov/29872004/) with respect to model parameters such as coordinates, ADPs (isotropic, anisotropic), occupancies, f' and f'', etc.

Here are a few places:

- reciprocal space:

cctbx_project/mmtbx/refinement

files:

minimization.py
occupancies.py
rigid_body.py
group.py

regression/tst_xray_fast_gradients.py
xray/boost_python/tst_xray.py
regression/tst_xray_derivatives.py

- real space:

cctbx_project/mmtbx/refinement/real_space/individual_sites.py
cctbx_project/cctbx/maptbx/tst_real_space_refinement_simple.py
cctbx_project/cctbx/maptbx/target_and_gradients.h
cctbx_project/cctbx/maptbx/real_space_refinement_simple.py

Note, these are examples of high-level code that uses target function and its gradients to perform various kind of refinement. You'll need to do some detective work to trace to the low-level code that actually calculates gradients. Hope that's good enough starting point for you.

Also, try grep for "gradient" and "target"! Usually tests (files tst*.py serve as good examples).

Good luck!
Pavel

On 10/3/23 08:13, Kristoffer Lundgren wrote:

Hello all,

I am wondering if it is possible to use cctbx to calculate gradients from experimental data? Both in reciprocal and real space is of interest.

Are there any code examples available somewhere showcasing how this can be achieved?

Best regards

Kristoffer Lundgren

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