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1fe73bab41 |
Model validation: scale fits on the GPU, change-of-basis probe gridded once per frame on all threads
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 |
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9ad92b6bfe |
Move the atomic-model code to image_analysis/structure_refinement/ and WriteModel to writer/
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 |
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a395f358ef |
1.0.0-rc.174 (#84)
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* Rugnux: Performance improvements on GPU and CPU (more of the pre-scan and of scaling on the GPU, faster CPU spot finding and crystal refinement), with unchanged results. * Rugnux: More robust processing - patches of persistently hot pixels are masked, an inconsistent merge triggers a retry at the measured beam centre, and builds targeting different CPU levels give the same results. * Rugnux: Improved scaling and merging - reflections with an overloaded pixel are dropped, as in XDS, sparse rotation sweeps are scaled more reliably, and French-Wilson amplitudes use an anisotropic Wilson prior. * Rugnux: Improved space-group determination - glide planes in groups without a centre of symmetry, screw axes from short or weak axial rows kept when a higher group is adopted, and more reliable decisions on twinned and pseudo-symmetric crystals. * Rugnux: Improved small-molecule processing - spots that grow wider than the integration disk and split spots are integrated over their measured footprint, sparse lattices are integrated on every frame, and the `.hkl` file holds unmerged scaled reflections (SHELX HKLF 4). * Rugnux: Reads Rigaku d*TREK SMV images (Saturn CCD), including detector 2theta and encoded pixel overflows; home-source (rotating-anode) datasets were added to the validation battery. * jfjoch_viewer: Fixed processing failing at the end with "Wrong JPEG library version" on Linux; the merge window shows the space group with proper subscripts and a checklist of crystal pathologies. Reviewed-on: #84 Co-authored-by: Filip Leonarski <filip.leonarski@psi.ch> |
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84228bf8be |
v1.0.0-rc.173 (#83)
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* jfjoch_broker: Optional per-dataset authentication - statistics, images and plots can require a bearer token, which jfjoch_viewer supports. * jfjoch_viewer: Dark mode and a theme-matched colour scheme, a magnifier panel, and simpler contrast and background controls. * Rugnux: Multiple performance improvements on GPU and CPU (CPU-only processing up to 40% faster, faster image decoding on ARM), with unchanged results. * Rugnux: `--model` rigid-body refinement runs on the GPU, and the model-validation check is faster and more reliable. * Rugnux: Improved scaling and merging - error model, outlier rejection, absorption correction and French-Wilson amplitudes now agree more closely with XDS and ctruncate. * Rugnux: Improved integration - radial background on powder and ice rings, crowded rotation data keep their reflections, and CPU-only builds integrate large unit cells as GPU builds do. * Rugnux: More robust detector geometry - measured beam centre, X-ray bandwidth and goniometer rate, and geometry refinement accepted only on significant evidence. * Rugnux: Merged files are written in the standard setting, or in the setting of a reference MTZ, structure-factor mmCIF or model, with its free-R flags. * Rugnux: Richer report - ice and powder rings, further lattices, superstructure candidates and mosaicity, with warnings worded as prompts to check. * Rugnux: Clear error messages when a data set needs more GPU or host memory than is available. Reviewed-on: #83 Co-authored-by: Filip Leonarski <filip.leonarski@psi.ch> |