The scale fit of every model-validation fit (fit_model: the real model, the indexing probe's relabellings
and every null replicate) was FitModelScale on the host - a long-double Levenberg-Marquardt per solvent grid
point, ~80% of the validation's CPU on a 400 A cell. It now runs on the GPU through ModelScaleGPU::FitSolvent,
the engine the rigid body and molecular replacement already use, from a small pool (ModelScaleGPUPool: up to
four engines with their own streams, sized on the card's total memory, at most an eighth of it). The grid,
the fits and the winner rule are FitModelScale's; the sums are taken in double on the device, so R-factors
agree with the host's to rounding. The CPU build, and a GPU build without a card, keep FitModelScale.
The change-of-basis probe gridded each candidate frame with gemmi's serial put_model_density_on_grid, once
for the data as merged and once more for each alternative indexing. It now grids each frame once, with
ModelGrid's parallel PutModelDensityOnGrid (the same grid, bit for bit), from threads outside the pool so the
gridding spreads over it, and scores every labelling on that F_calc. Exact.
4nwv (122k atoms, I222, 400 A cell): model validation 33.2 s -> 14.0 s; every logged R, sigma and decision
the same.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01EizBKhTqrAYago9KJG3dA3
The model scale searched b_sol only over 10-80 A^2. That is the range
Fokine & Urzhumtsev report for models at ordinary B, but on low-resolution
entries whose deposited B is 200-400 A^2 the fit sat on the 80 A^2 ceiling
(and k_sol on its 0.1 floor): a solvent edge far sharper than the atoms it
lies against, reaching too deep in resolution. R-free came out 0.05-0.10
above REFMAC (0 cycles) and phenix.model_vs_data on the same MTZ, model
and flags.
The ceiling is now max(80, 2 x the model's mean atomic B) (SolventBMax),
for the reported fit and for the rigid-body placement's per-zone solvent
(CPU, GPU and the host fallback alike). The grid keeps eight b_sol values
across a wider box, so it costs no more points; the default box, and so
every model with mean B <= 40 A^2, is bit-identical to before.
Measured (10 open-arm sets with --model, GPU build, vs the same base):
high-B set, 7.0 A: R-free 0.462 -> 0.364, b_sol 80 -> 379 (REFMAC 0.366,
REFMAC's own b_sol ~371; model_vs_data 0.291);
the rigid-body step now commits
high-B set, 3.9 A: 0.410 -> 0.331, b_sol 80 -> 388, k_sol 0.10 -> 0.225
(REFMAC 0.328, model_vs_data 0.314); null 10.1 -> 14.2 sigma
B~200 set, 3.2 A: 0.408 -> 0.402, b_sol 80 -> 120; enantiomorph label
decision unchanged (27.2 -> 25.8 sigma)
7 other sets (mean B 16-57): bit-identical R, k_sol, b_sol, placement.
p.hkl md5 and the MTZ reflection data are identical to the base on all 10.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
A pure move. ModelValidation, RigidBodyRefine, RigidBodyGPU, ModelFFT, ModelGrid,
ModelScaling, ModelMaskGPU, ModelScaleGPU and SigmaA - everything that works on an
atomic model - become the JFJochStructureRefinement library, linked by
JFJochImageAnalysis. WriteModel (the placed-model mmCIF/PDB writer) goes to writer/
as its own small JFJochModelWriter target, so JFJochWriter, which a writer-only build
compiles, does not gain a gemmi dependency. Only include paths and CMake lists change.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01SVmAWnzCmRKAXVUCdc4iNi
leonarski_fandClaude Opus 5.5