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leonarski_f	07c8b2ddd4	docs: the Rugnux card and the naming table mention refinement and live collections ... Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit f8d07397288137dd5e3a0e5c101f2036d51228bd)	2026-10-26 14:50:42 +01:00
leonarski_f	c3c5a32a0d	docs: rugnux getting-started pages - refinement, the full output list, a troubleshooting note ... RUGNUX: a model run also refines the model it placed; the model can be given as an input; only the unmerged MTZ is written by default; the _process.h5 is not a default output; a short "when a run fails" note. TUTORIAL: the .ins, the refined model/maps/blobs, the log and _modules.h5 in the output list; the report is not written with -o ""; stills: -X Auto picks ffbidx with a cell, a run over several files. FORMATS: the XFEL stills formats and model/reference inputs told by content. CALIBRATION: -C and -S as the calibrant. INSTALL: the CPU path runs every indexer and the refinement. MODEL_AND_REFERENCE: the refined model is written as .pdb too. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit 0062d72b95e996438ddc65dc343b526c84daa7fb)	2026-10-26 14:50:42 +01:00
leonarski_f	8edd0e5f3e	docs: rugnux options, model and export pages brought in line with the usage text ... RUGNUX_ADVANCED: --simulate-live/--fast-live rows, -e exclusive, stills behaviour of --beam-center-check, -S, --min-partiality (0.5), --capture-uncertainty, --adaptive-integration-radius (on for stills too), --detector-distance/--rot1/--rot2/--no-refine-tilt; --background-radial auto as it decides now; --refine-modules syntax; _cell.*_esd. MODEL_AND_REFERENCE: the default refinement of a placed model in the summary, the decision table and the step list; --mode scale does not refine. INTEGRATION: the .ins written beside every .hkl (ZERR on rotation). VIEWER: rugnux writes _process.h5 only with --no-merge/--write-process-h5. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit 51d2564356ba46bda8730c855ff8d3ee7c23d605)	2026-10-26 14:50:42 +01:00
leonarski_f	d8c14046b2	rugnux: unit-cell e.s.d.s - ZERR in a new SHELX .ins beside the .hkl, _cell.*_esd in the mmCIF, CELL_ESD_* in the report ... Rotation runs now estimate the standard uncertainties of the cell. Every strong integrated observation (I > 3 sigma, unclipped, unsaturated, off ice rings) gives |q| = 1/d at its observed centroid, which depends on the detector geometry only; q^2 = h^T G* h is linear in the reciprocal metric, so the components of G* the point group leaves free (projected from the group's rotation parts, any setting) are fitted by weighted linear least squares with 4-sigma rejection, and the GoF-scaled covariance is carried analytically onto a, b, c, alpha, beta, gamma (ties give equal e.s.d.s, fixed angles zero). Least-squares cell e.s.d.s are known to be too small (Herbstein 2000), so the same fit is made on 8 blocks of consecutive frames and their scatter / sqrt(8) is the second estimate; the written e.s.d. is the larger of the two per parameter. Stills get none. Outputs: <prefix>.ins next to every .hkl (TITL, CELL at the wavelength, ZERR with Z = order of the group, LATT/SYMM from the space group - positive LATT only with -1 at the origin - a placeholder organic SFAC/UNIT at 18 A^3 per non-H atom, HKLF 4, END); the mmCIF gains _cell.*_esd ("." where fixed) and _cell_measurement.reflns_used/theta_min/theta_max, and writes the cell to 4/3 decimals; report keys CELL_ESD, CELL_ESD_LSQ, CELL_ESD_BLOCKS, CELL_ESD_BLOCK_COUNT, CELL_ESD_REFLECTIONS, CELL_ESD_THETA_RANGE_DEG (+ dev CELL_ESD_OBSERVATIONS, CELL_DSPACING_FIT). On 13 small-molecule sets the block scatter is 10-40x the least-squares e.s.d. and is what gets written; it lands within ~0.3-5x of XDS's CORRECT.LP e.s.d.s. SHELXT solves from the generated .ins and SHELXL carries ZERR into its CIF su. Costs 12 ms on a small molecule, 0.16 s on 690k lysozyme observations. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit e74a3be76261fe1b6c0ff7b80c21afc4768c46cd)	2026-10-26 14:33:38 +01:00
leonarski_f	22debb1be6	docs: the stills rocking-curve datasets in the _process.h5 master ... Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit 1195b9be6e0ca66774774f6de4867180b7bd0a47)	2026-10-26 14:09:32 +01:00
leonarski_f	e6b550fe42	Tests: the stills rocking width - the window at a reflection's resolution, _process.h5 round trip ... StillsPartialityRefine_MeasureRunWidth_WindowAtReflectionResolution, JFJochReader_StillsRunWidth. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit dafb8d1bf996d1000741eecf019aee780dd91ebe)	2026-10-26 14:09:32 +01:00
leonarski_f	8a123e794d	Stills: the run's rocking curve goes to _process.h5 and --mode scale merges with it; MeasureRunWidth takes the window at each reflection's resolution ... --mode scale re-measured the rocking width on the stored reflections, so on any file whose frames were predicted through the run's curve it merged with a different curve than the mx run did. The curve the post-refinement used (formula, table, radial scale) is now carried in the EndMessage (StillsRunWidth) and written to the master: /entry/MX/stillsRockingWidthFormula [gamma0 1/A, gamma_e rad, bandwidth sigma], /entry/MX/stillsRadialScale, /entry/MX/stillsRockingWidthTableDstar and /entry/MX/stillsRockingWidthTable (1/A). The reader returns it, and --mode scale passes it to the post-refinement. A file without it is re-measured as before. MeasureRunWidth grouped each frame's reflections by the frame's window, taken as the largest excitation error it predicted. With a window that follows sigma(d*) that is the high-resolution window, applied to the frame's low-resolution reflections too. Given the curve the frames were predicted through, the window is now that curve at the reflection's own resolution; without one, the frame's largest excitation error as before. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit 992343d0206489991880bb927efc79131134a1d9)	2026-10-26 14:09:32 +01:00
leonarski_f	00662c4110	Refinement: common cofactors and modified RNA nucleotides in the embedded dictionary; heme iron restrained from LINK records ... The embedded CCP4 Monomer Library subset grows from 62 to 84 compounds: - the modified tRNA/rRNA nucleotides PSU, 5MC, 1MA, OMG, OMC, OMU, H2U, M2G, 7MG, 2MG, 5MU (RNA group, joined by the library's backbone link "p"); - the cofactors NAD, NAI, NAP, NDP, FAD, FMN, HEM, HEC, SAM, SAH, and dioxygen (OXY). CMO is left out: its dictionary has C-O at 1.25 A, where bound CO is near 1.15 A. links_and_mods.cif gains the links these compounds use: HEC-CYS1/HEC-CYS2 (heme C thioethers), CYS-HEMB/CYS-HEMC, CYS-FAD and HIS-FAD1/2, with their modifications. AddMetalLinks now takes a metal atom of any residue, not only a one-atom ion, so a heme iron's LINK records to His NE2 / Met SD / water become bonds at the library's metal-site distances; the site's coordination counts the metal's bonds in its own dictionary (a heme's four pyrrole N) as well as the records. A metal within a ligand is also a metal for the repulsions (1.9 A to N, O, S) and its dictionary bonds are kept with the metal bonds. Note HEC.cif's own Fe-N(pyrrole) ideal is 1.90 A (HEM: 2.04 A), so a cytochrome c reports a metal-bond rmsd near 0.1 A. Test RefinementRestraints_deposited_ligands builds the topology of eleven deposited models cut down to the ligand and its surroundings (tests/test_data/ligands, 66 KB, from PDB 1EHZ, 8BKH, 6K9I, 2W3V, 5VML, 6F3P, 8CON, 3TK0, 7TCD, 6W4H, 5EPE): every ligand restrained, bond rmsd < 0.03 A, the RNA backbone bonded to each modified nucleotide, the heme Fe-His bonds, and the HEC thioethers. rugnux --mode refine on the full entries against their deposited structure factors: R-free within +-0.003 of the build where these were held fixed, ligand bond rmsd vs the dictionary from 0.004-0.058 A down to 0.002-0.042 A. rugnux grows by 425 KiB. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit f4d407c8de6cb462320edb21a70665350e436d28)	2026-10-26 13:56:29 +01:00
leonarski_fandClaude Opus 5.5	d90bc68085	CI: the documentation also pushed to the gitea-pages branch of rugnux/gitea-pages, on every push for now (token test) ... Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu	2026-10-26 11:39:10 +01:00
leonarski_fandClaude Opus 5.5	771e669f75	rugnux usage: -S on serial stills also settles the indexing ambiguity from the data ... Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu	2026-10-26 11:16:34 +01:00
leonarski_f	6491cc5a7e	docs: serial-stills indexing ambiguity described the same way everywhere ... Two mechanisms, as the code has them: with -S and no reference or model, the crystals made consistent from the data (Brehm & Diederichs objective, cell-metric anchors); with -z or --model (-C/-S), per image against the reference, crystals their own cell decides keeping that indexing, the data-only result as a check. Removes the statements that the ambiguity needs a reference or model (tutorial, quick start, overview, §10.9), adds the anchoring to the reference/model rows, the "no -S" case (mixed merge, can pass for higher symmetry, warning), and the report keys in the reference case (AMBIGUITY_DATA_DISAGREES in place of AMBIGUITY_REINDEXED, AMBIGUITY_TIME_S, none in --mode scale). Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit 8db1d3ecb97dba90471c4db238aff632d11bc3e8)	2026-10-26 11:15:54 +01:00
leonarski_f	0cc3129650	docs: refinement's GPU engine in GPU data analysis, refinement in the pipeline figures ... GPU_DATA_ANALYSIS.md: the refinement section at the level of the other engines - density gather, cuFFT r2c/c2r, compose + likelihood target, CSR adjoint, warp-per-atom gradient, restraints and slot gather, fine mask and robust scale fit (on-device median), reductions and determinism, stream priority and blocking-sync waits, trial slots over cards, DeviceBytes budget, CPU fallback, no Metal; indicative RTX 5080 timings. Pipeline figures: a dashed Refinement box after Structure & map on both, the model branch labelled as deciding nothing; the stills row gains the indexing-ambiguity step before the first merge. RUGNUX_OVERVIEW.md: captions, a refinement paragraph, refined outputs under Write. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit 8645fb2aca1abbbddec29cdfa99056471f8f38a5)	2026-10-26 11:15:54 +01:00
leonarski_f	e406eb17ea	docs: refinement chapter (§15), REFINE_ report keys, acknowledgements and in-source credits ... - New docs/CPU_DATA_ANALYSIS_REFINEMENT.md (§15): the ML amplitude target and its FFT gradient, scale/robust fit/fine solvent mask, D and the variance (work/free), the embedded Monomer Library subset and topology, geometry/metal/KL-B restraints, the minimiser, the weight trials, refined maps, blobs, GPU/CPU, and a "Not yet" list; with its own References. Linked from TECHNICAL.md and CPU_DATA_ANALYSIS.md; §14 no longer says the structure is never refined. - RUGNUX_REPORT.md: a Refinement (REFINE_*) section - every REFINE_ and REFINE_SCORE_ key, the --mode refine input keys and the _blobs.json fields. - RUGNUX_MODEL_AND_REFERENCE.md: "What it does not do yet"; RUGNUX_ADVANCED.md: --model mentions the refinement, --no-refine as in the usage, a --mode refine options table; GPU_DATA_ANALYSIS.md: the refinement's CUDA engines and the missing Metal path. - ACKNOWLEDGEMENT.md: Brunger, Karplus & Petsko 1989 (gradient-balanced starting weight), Nocedal 1980 (two-loop recursion), Charbonnier et al. 1997 (pseudo-Huber), Jiang & Brunger 1994 (flat solvent mask), Kullback & Leibler 1951; all DOIs checked against Crossref. - In-source credit lines: the weight balancing (replacing a "Brunger (1992)-style" line that named the R-free paper), Nocedal 1980, Charbonnier 1997, Jiang & Brunger 1994, Emsley et al. 2010 at FindDensityBlobs, Read 1986 at the refined maps. Comments only. - docs/THIRD_PARTY_NOTICES.md regenerated from the root file with update_version.sh's own step (it lacked the CCP4 Monomer Library row). Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit 09375dba351bae0cc73e9a6f0f79455dc92b3a10)	2026-10-26 11:07:43 +01:00
leonarski_f	f960bd7a80	Docs landing page: a real diffraction frame in the hero, and the command with a model ... The generated spot-and-ring drawing is replaced by one 0.2 deg rotation frame of the in-house lysozyme standard (EIGER2 16M, SLS X10SA): Bragg spots on their lunes, the beam stop and its arm, the module gaps. docs/landing/hero_frame.py makes the 920 px WebP (67 KB) from the master file - crop about the beam centre, log tone map from the frame's own background, block mean+max downsampling - and is run by hand; the WebP is committed and copied by the landing-page step. The dark theme shows it inverted through a CSS filter. The hero's command line drops its explanatory sentence and gains the second form, rugnux <diffraction image file> <CIF/PDB model file>. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit ff26000bfe7446cb4fda739c3b72596f8a8b7047)	2026-10-26 10:53:25 +01:00
leonarski_f	4dbcb35708	Stills partiality: the rocking width measured in shells of equal width in d*, used as a table ... MeasureRunWidth measured the width in eight shells of equal count in d*^2 and fitted the three-term formula gamma0^2 + (gamma_e d*)^2 + (bw |q_z|)^2 to them. On runs predicting ~1000 reflections a frame the equal-count shells all sat at 3.8-1.8 A, so the low-resolution width was the formula's extrapolation, and the fit's form flipped with the number of frames (to a pure bandwidth at 50k frames). The same window-group moment is now also measured in eight shells of equal width in d*, made non-decreasing (pool adjacent violators, weighted by each shell's summed signal) and kept in RunWidth as a table that the partiality interpolates linearly in d*. The formula is still fitted on the equal-count shells and still sets the prediction window. With fewer than three measurable shells the formula is used as before. Still battery, 12 non-float sets, together with the sigma-following prediction window (the previous commit; run 20261026-1021_1b28d6_still-part-comb against rc180 20261026-0857_3882b0_still-part-base1, 0-cycle REFMAC R-free vs deposited, both --no-refine): 6 better, 3 unchanged, 3 worse (by 0.002), sum of changes -0.027 (the window alone: -0.007); largest gains pal90 -0.014, alvra103_int16 -0.011, lcls222 -0.005; largest losses euxfel152 +0.005, alvra213_int16 +0.005 (+0.010 with the window alone), euxfel83 +0.003. Win/draw/loss against the depositions unchanged at 9/2/1. Rotation: p.hkl byte-identical on 5reo, lyso_x06da_ref and thau_x10sa_16keV. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit de779bb10b1813eeae625e3994b1ca73d6079d7a)	2026-10-26 10:50:52 +01:00
leonarski_f	0829b9a72d	Stills prediction: every frame predicts through two rocking widths of the run, measured first and centred on its radial scale ... Each still predicted through |dist_ewald| <= 2x its own profile radius (the RMS excitation error of its indexed spots): one width at every resolution, differing eightfold between frames. Against the run's measured rocking width that was 5-8 sigma at low resolution on one SACLA run (59 % of the 40-8 A predictions empty) and below one sigma at high resolution on a crowded LCLS run (half of the curve never integrated). Now the stills image pass first integrates a sample (a tenth of the run, at least 2000 frames) the old way, scales it against its own merge and measures the run's rocking curve on it - centre (MeasureRadialScale) and width (MeasureRunWidth), as the merge measures them - then predicts every frame through 2 sigma(d) of that curve, centred on the reciprocal lattice scaled by the radial scale (BraggPredictionSettings::window_*, CPU and CUDA). The post-refinement uses the same curve instead of measuring it again: re-measured through windows that follow it, the constant term falls to ~0 and the result swung by up to +-0.015 per run. Still battery, 12 non-float sets, against the st-partial baseline (0-cycle REFMAC R-free vs deposited): 9 better, 3 worse, sum of changes -0.013; the off-centre run -0.012, worst +0.008 on one JUNGFRAU run (its sample measures a different width form than the full run). Integrated reflections 0.8-1.7x, battery wall +13 % on a loaded box. Rotation untouched (window fields zero unless set); p.hkl byte-identical on three rotation sets. Tests: BraggPrediction_WindowFollowsResolution, BraggPrediction_CPU_GPU_consistency_window. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit 1b28d671d780bc88525ceac5120017963d937bbc)	2026-10-26 10:50:52 +01:00
leonarski_f	13da79b788	Refinement GPU: the atom gradient kernel walks its box without integer division ... Bitwise. One warp per atom, each lane taking the box's points t = lane, lane + 32, ...: every point cost three integer divisions/modulos to turn t into (u, v, w) and three more (imod) to wrap them into the grid. The lane now steps (iu, iv, iw) on by 32 points with adds and carries, and wraps from the box's first point, wrapped once per atom (a box is narrower than the cell, so one conditional subtraction per axis). The same points in the same order per lane, the same arithmetic. atom_gradient_kernel (nsys, side by side): 5reo 426 -> 237 us, 5f6m 887 -> 523, 9yl4 1436 -> 802, 7d98 692 -> 388 us per launch. Refined CIF md5 unchanged on the 5 GPU cases; side by side = one at a time. Wall: 5reo 1.43 -> 1.35, 5f6m 2.20 -> 2.00, 9yl4 6.88 -> 6.82, 7d98 3.58 -> 3.38, 5f6m MD start 4.16 -> 3.71 s. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit 6554e9dcbe4b448eda582eb76d6a24c59fe6ab0c)	2026-10-26 09:16:34 +01:00
leonarski_f	4a8e13ddfa	Refinement GPU engine: its waits on the stream asleep (blocking-sync event) rather than spinning ... Bitwise. cudaStreamSynchronize spins a core for the whole wait; the weight trials' engines wait on a shared card for most of a run, so about half of the user cycles of a refinement were the spin (PROFILE.md: 38-50%). A StreamWaiter (CUDAMemHelpers.h: an event made with cudaEventBlockingSync, recorded and waited for) now takes the refinement engine's waits - evaluation, Fcalc, Fmask, the uploads of positions, row model, blur and restraints. The short waits of the host-driven loops stay spinning: the scale fit's Levenberg-Marquardt (one launch of 66-120 us per step) and the gather's pair count; making those block too cost 2-3% of wall (wake-up latency), here the wall is unchanged. No process-wide cudaDeviceScheduleBlockingSync: that would change every GPU wait of the broker. CPU use (-N 8, time -v): 5reo 301-315% -> 190%, 5f6m 326% -> 181%, 9yl4 333% -> 222-228%, 7d98 307% -> 181%, 5f6m MD start 309-320% -> 151%. Wall, two interleaved runs each: 5reo 1.43-1.52 -> 1.43, 5f6m 2.19-2.20 -> 2.19-2.20, 9yl4 6.83-6.84 -> 6.88-6.89, 7d98 3.50-3.51 -> 3.58, 5f6m MD start 4.16-4.34 -> 4.16 s. Refined CIF md5 unchanged on the 5 GPU cases; side by side = one at a time. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit d23d2cf7bb99b30617a3f57c531b03db8bc03e05)	2026-10-26 09:16:34 +01:00
leonarski_f	f34d2f4cca	Refinement: the weight trials' own slots made while the placement runs ... Bitwise. MakeOwnSlot copies the model as it was before the topology and reads only what the placement does not change (cell, reflections, the engine's kind, the B ceiling), so the slots are now built on their threads right after the start score, beside the rigid-body and group-B placement, and joined where they were built before (also where the placement throws). The "slots" stage goes from 0.23 s to 0 on 9yl4; the placement is not slowed (0.59 -> 0.60 s). Refined CIF md5 unchanged on 5reo, 5f6m, 9yl4, 7d98, 5f6m MD start (GPU) and 6o2h (CPU); side by side = one at a time. Wall: 5reo 1.46-1.53 -> 1.54, 5f6m 2.26 -> 2.21, 9yl4 7.03 -> 6.83, 7d98 3.65 -> 3.56, 5f6m MD start 4.20 -> 4.15 s. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit 0752a921a4293d4213894e3242c4ef36d8ce2a05)	2026-10-26 09:16:34 +01:00
leonarski_f	1f8b5b1986	Refinement: a Refit's solvent grid starts around where the context's last one ended ... Logic change (deterministic), kept on evidence. Every Refit searched the whole k_sol/b_sol box - an 88-point coarse pass of plain least squares, then the robust fine pass around its winner. ModelScaleBox (and ModelScaleGPUPool::Fit / ModelScaleGPU::FitSolvent) take an optional start; with one, the coarse pass is skipped and the fine pass is laid around it. Refinement passes the grid winner of the context's previous Refit (before MoveOverallB moves the overall B into b_sol); it travels with a trial's fit, and a trial's first Refit without one (Context::ForgetStarts, which also clears the likelihood's D start) searches the whole box, so a trial still depends on nothing its slot ran before (side by side = one at a time, md5). Evidence (GPU, -N 8): full refinement of the 14 parity sets from their placed models - 12 refined CIFs identical (md5), 9ig7 and 6iu9 differ, final R-work/R-free equal to 4 digits but 6iu9 R-work 0.2911 -> 0.2910; of the 5 timing cases 4 identical, 7d98 (cif start) R-free 0.3096 -> 0.3095; 5f6m MD starts 01-04 median R-free 0.1692 -> 0.1692; 6o2h on the CPU engine identical (md5). The score-only parity table is not touched (one Refit, no start). refit.scale (TIMING sum): 5f6m 1.52 -> 1.10 s. Wall: 5reo 1.68 -> 1.53, 5f6m 2.43 -> 2.24, 9yl4 7.19 -> 7.02, 7d98 3.70 -> 3.65, 5f6m MD start 4.57 -> 4.22 s. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit ff285fb525ecf4b480698d4aafe212a34301a8fe)	2026-10-26 09:16:34 +01:00
leonarski_f	1f1aa18b67	ModelScaleGPU: the robust fit's median of the residuals on the device ... Bitwise. The first robust round copied every fine-pass fit's residuals to the host (up to 25 x n floats, 9 MB at 92k reflections) and took std::nth_element of each there. The median is now a radix selection on the card (one block per fit, four byte-wide passes of integer counts over the float bits - the residuals are not negative, so the bits order as the values): the element nth_element puts at n / 2, the same value; only the fits' c come back. FitSolvent and RobustBatch lose the host threads they took for it. Refined CIF md5 unchanged on 5reo, 5f6m, 9yl4, 7d98, 5f6m MD start. Wall (-N 8, quiet): 5reo 1.72 -> 1.68, 5f6m 2.57 -> 2.43, 9yl4 7.28 -> 7.19, 7d98 3.78 -> 3.70, 5f6m MD start 4.76 -> 4.57 s. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit dc53896c335fdabdf4d417323038e05b8b63535d)	2026-10-26 09:16:34 +01:00
leonarski_f	ca0a6dd343	Refinement: each slot's likelihood fit on all of the run's threads ... Bitwise (the bins are fitted independently: the same bits at any thread count). The weight-trial slots Refit in lockstep while the GPU idles, each with its 1/slots share of -N for the ML bins; the bins now go to the shared worker pool with -N tasks per slot, so the threads of slots that are not fitting help the ones that are. After the Newton searches (previous commit) the ML fit is 0.1-0.5 s summed over a run, so the wall gain is within noise: 5reo 1.63-1.75 -> 1.72, 5f6m 2.60 -> 2.57, 9yl4 7.34 -> 7.28, 7d98 3.78 -> 3.78, 5f6m MD start 4.82 -> 4.76 s. Refined CIF md5 unchanged on 5reo, 5f6m, 9yl4, 7d98, 5f6m MD start (GPU) and 6o2h (CPU). Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit 56815f5390cc01e8da5d420fff73cdf4394c385c)	2026-10-26 09:16:34 +01:00
leonarski_f	2c1df0ebfa	Refinement: the likelihood's D and beta searches by Newton's method; D on the working set from the last fit's ... Deterministic, rounding changes. The per-bin ML fit took 4 rounds x (40 + 40) golden-section steps on the free set and a 50-step golden section for D on the working set - each step a Bessel I0/I1 per row, ~4.6M per Refit at 92k reflections, 27-37% of a trial's wall on the high-resolution sets. Each one-dimensional search is now a safeguarded Newton iteration on the analytic first and second derivatives (bracketed on the sign of the derivative, bisection where a step leaves the bracket or the curvature is not positive), within the same brackets; the free-set alternation keeps its 4 rounds from the moments, so beta is the one it was (a converged joint fit was tried: the 4 rounds are not converged in the low-resolution bins, and converging them moves 6iu9's FOM by -0.003, so it was not kept). D on the working set starts from the bin's D of the context's previous Refit (XrayRowModel::bin_d), restored with a trial's fit and cleared at a trial's first Refit, so a trial depends on nothing its slot ran before (side by side = one at a time, md5). 14 parity sets, score only: R-work/R-free identical to 4 digits, mean |FOM - REFMAC| 0.01186 -> 0.01186, D within 1e-5 and var within 1e-4 (relative) per reflection. refit.ml (TIMING sum, -N 8): 5reo 1.47 -> 0.11 s, 5f6m 3.88 -> 0.26, 9yl4 1.37 -> 0.11, 5f6m MD start 4.97 -> 0.46. Wall: 5reo 2.03 -> 1.75, 5f6m 3.45 -> 2.60, 9yl4 7.99 -> 7.36, 7d98 4.04 -> 3.78, 5f6m MD start 6.10 -> 4.82 s. 5f6m MD starts 01-04 median R-free 0.1693 -> 0.1692. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit a91511945e0ccd7145a93877c0c231e87f86fb44)	2026-10-26 09:16:33 +01:00
leonarski_f	a8d3a8dbc2	Refinement: the mask grid sized without allocating it; the L-BFGS pairs keep their s.y ... BulkSolventMask::MaskGrid, documented as "sizes and spacing set, values not allocated", allocated and zeroed the whole fine mask grid (up to 2^26 floats) - in BulkSolventMask's constructor and in every GPU engine's, i.e. once more for each weight-trial slot, only for the grid's size. It now takes good_grid_size() as set_size_from_spacing() does, and the CPU engine's Fmask() allocates its copy. rugnux_refine_test, RTX 5080, -N 8: 9yl4 8.6 -> 7.8 s, 7d98 4.85 -> 4.0 s (engine 0.66 -> 0.16 s, slots 0.60 -> 0.23 s on 9yl4); the high-resolution sets, whose mask grid is small, are unchanged. RefinementMinimiser keeps s.y of every pair it stores and Direction() takes rho and gamma from it instead of two more dot products per pair per call (the same Dot() of the same vectors): Direction's CPU time -22% on 9yl4; no wall change with the trials side by side, where other slots fill the card meanwhile. Bitwise: refined CIF identical on 5reo, 5f6m, 9yl4, 7d98, a 5f6m MD start (GPU) and 6o2h (CPU engine). Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit 6f5caf5e1b1183a752acc5cca78bfb7ef002b12a)	2026-10-26 09:16:33 +01:00
leonarski_fandClaude Opus 5.5	6da51dc5d7	rugnux: no --refine flag - a placed model is refined by default, --no-refine skips it ... Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu	2026-10-26 06:54:15 +01:00
leonarski_f	3882b0f062	Serial stills with a reference or model: crystals their own cells anchor keep that indexing ... The per-image reference/model choice of indexing ignored the crystals' refined cells. On a pseudo-merohedral cell, where at least 90% of the crystals' cells fit the run's cell better as indexed than after a twin law, the cells decide that law - the rule the data-only resolution already uses (AnchorOnCells, factored out of ResolveReindexReferenceFree and shared). The resolver now keeps each image's CC per indexing (IntegrationOutcome::reference_cc); before the stills merge, AnchorReferenceReindex puts every image back as indexed, applies the cell rule, and lets the reference choose only among the indexings left open. Exactly merohedral lattices (no metric signal) are unaffected. Still battery (REFMAC 0-cycle R-free, model before -> anchored; data-only in brackets): pal90 0.1883 -> 0.1834 (0.1832), alvra213 0.2073 -> 0.2011 (0.2013), alvra213_int16 0.2081 -> 0.2021 (0.2024); euxfel83 0.2037, euxfel152 0.2452, sacla237, lcls222 unchanged; lcls242_t 0.2847 -> 0.2952 (0.2942): there the model had moved about half the crystals against cells that decide all three laws (96/96/100%). Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit 85c804676ffd15ffd66e2ba05928000d6f4e765f)	2026-10-26 06:49:20 +01:00
leonarski_fandClaude Opus 5.5	ba52aadbce	rugnux: the geometry refinement algorithm is -r, --geom-refine; --refine was declared twice and its no-argument form shadowed it ... Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu	2026-10-26 06:49:20 +01:00
leonarski_f	a78bfe951d	rugnux: a model and a reference among the inputs, in any order, told by their contents ... `rugnux <images> <model> <reflections>` in any order, without --model or -z. Each positional file is classified by its contents (RugnuxInputKind.h, in JFJochRugnuxOutput - the library still reads no files): an MTZ (magic) or an mmCIF with a _refln / _diffrn_refln loop is reference data (-z; the input itself in --mode refine), a PDB file (a PDB record first, then ATOM/HETATM) or an mmCIF with an _atom_site loop is a model (--model), anything else is images for the readers. CBF (###CBF or _array_data) counts as images; a file whose first line is neither data_ nor a PDB record is decided there, so image files are not read through. An mmCIF holding both atoms and reflections is refused as ambiguous. At most one model and one reference, --model/--mr and -z included. Gzip read through. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit 8f844b0bf86f338d20e8aed426a387722dd8d7cc)	2026-10-26 01:38:25 +01:00
leonarski_f	794db0ca34	Refinement cut by the run's cancel; the hero shows the refined R-work / R-free ... The refinement of a placed model gets the run's cancel flag (RefinementSettings::cancel, through CancelFlag::RunFlag), so the broker's deadline or a cancel - and Ctrl+C in rugnux - cuts a running refinement short with what its finished trials found. RefinementResult::cancelled goes to the live status as rugnux_live_refinement.cancelled (API, regenerated clients) and to the step's note. Hero: once refined, the model card's headline is "R-work / R-free, refined" (e.g. 0.32 / 0.35), its green/red still the placement verdict, the placement and fit in the context line. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit 395016a30c2bc2aa26fdf2cec2ced9cebe6fad80)	2026-10-26 01:38:25 +01:00
leonarski_f	baec34685d	Rugnux live: the uploaded model is refined after placement; refined scores, model, maps and blobs in the status, the viewer and the hero ... The live run refines a placed model as `rugnux` does (ProcessConfig::refine), after every decision and before the end message; a cut before it starts leaves it out, as the model. The writer still gets the placed model; the refined one stays with the broker. API (broker/jfjoch_api.yaml): - rugnux_live_model.refinement (rugnux_live_refinement): performed, reason, on_gpu, seconds, r_work, r_free, rmsd_bonds_A, rmsd_angles_deg, blob_count, blobs (at most 50, rugnux_live_blob: kind, x, y, z, peak_sigma, volume_A3, nearest_atom, nearest_atom_distance_A) - rugnux_live_status.refined_model - /rugnux/model.cif and /rugnux/map.ccp4 take stage=placed|refined, by default the refined model where there is one; the anomalous map stays on the placed model's phases (the refined coefficients carry none). Regenerated broker/gen, frontend/src/client, redoc, and the python client docs (which also brings the hero fields and rugnux_live_model it was missing). Frontend: the model card keeps its green/red and gets "R-free 0.xx (refined)" as its context line, "refining..." while the step runs; the model section adds refined R-free and blob tiles; Mol* shows the refined model and maps, with the blobs as small spheres coloured by reading (switch, off at first). The Refinement step is in the timeline like any other. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit 3b47fb9a53b7dfad1c1ed289e169094c8d3d9d3e)	2026-10-26 01:38:25 +01:00
leonarski_f	7bf906e4a2	rugnux: a placed model is refined by default - giving a model is the opt-in ... Refinement (Refinement.h) now runs whenever --model or --mr places the model (rigid body fits, or molecular replacement placed it), on the GPU or the CPU: a run that should not spend the time is given no model. --no-refine skips it (for debugging); --refine is still accepted and ignored. A model that was not placed (rejected by the rigid body, not placed by MR - e.g. the battery's wrong-model null) is no longer refined. Processing-inert as before: it runs after every decision; R_WORK/R_FREE and every key outside REFINE_ (section 5), and <prefix>.mtz / _model.cif / _maps.mtz, are unchanged. The block moved after the placement notes so they stay on the step that placed the model. The viewer's processing jobs refine too. The equivalent command line gives --no-refine back where refinement was off. Battery: score.py reads keys exactly, so REFINE_R_FREE cannot alias R_FREE; new report-only fields rfree_refined, rwork_refined, refine_s (part of rugnux_wall_s), shown in the per-set table. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit b0bb741831f517b553e59152b3b482a3f75d953a)	2026-10-26 01:38:24 +01:00
leonarski_f	3b06bcee78	Refinement: the trajectory ends at its best step, steps try the positional weight halved too, the final ladder must win ... Three changes to how the trajectory of commit 2bfb84bc4 moves and ends: - A step is taken while its trial lowers R-free or R-work by more than the tie and its R-free stays within the tie of the best so far; the trajectory then ends at its best step. On a deposited model, whose free set it was fitted to, R-work falls while R-free rises, and the trajectory now ends where it began instead of walking on while R-work falls. - Positional steps try the weight halved as well as doubled: at a fixed weight the geometry loosens as the model improves (the X-ray gradient grows with D) until the trials leave the bounds, which stopped 8dqb's trajectories at 2 A (angles > 2.0 deg at w0/128 by step 6). - The final ladder's choice replaces the trajectory's end only where it displaces it (geometry within bounds, R-free lower by more than the tie); before, its first rung was taken by default, two more cycles of movement that on deposited models cost R-free. Deposited models (14 parity sets), R-free after refinement vs refine-combined: mean +0.0058 -> +0.0016 (e.g. 7n2s +0.012 -> +0.003, 9rcs +0.013 -> -0.008, 7d98 +0.015 -> +0.003, 9yl4 +0.010 -> +0.003), the time halved against refine-combined. MD starts, median R-free (REFMAC 0-cycle scorer), previous commit -> this: 5f6m 0.167 -> 0.168, 8dqb 0.294 -> 0.297, 7arr 0.278 -> 0.290 (REFMAC 0.311), 11if 0.244 -> 0.245, 5reo 0.258 -> 0.259, 7d98 0.335 -> 0.335. Determinism: run A == run B == --trials-at-once 1 on 5reo, 9rcs and a 5f6m MD start. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit c2b55aab1aaff637d9484dec0d25003b5c4a3857)	2026-10-26 01:38:24 +01:00
leonarski_f	bda90dbdd5	Refinement: B restraints in proportion to B (Kullback-Leibler form) with contacts, an own ADP weight, overall B into the atoms ... - B similarity: E = (B_i - B_j)^2 / (kappa^2 B_i B_j), the symmetric Kullback-Leibler divergence of two isotropic Gaussians (Murshudov et al. 2011), so sigma = kappa sqrt(B_i B_j) instead of a fixed 1.5-4.5 A^2. kappa 0.1 / 0.133 / 0.2 / 0.3 for main-chain bonded / angle-related and side-chain pairs (REFMAC's logs list sigma ~0.1 B for main-chain bonded pairs at B 11-140; the ratios are those of the old sigmas, which these equal at B = 15). New class: atoms within 4 A that no bond or angle relates, waters and symmetry mates included, kappa 0.5 (BuildBContacts, sharing the neighbour search with BuildRepulsions). CPU and GPU. - The B factors' X-ray weight is balanced on its own (BalancedADPWeight: B-restraint over X-ray B-gradient on the model with B shaken by 20%) instead of being a multiple of the positional weight; the ladder tries B held and refined at that weight, the trajectory's B steps divide and multiply it by four, positional steps and the final ladder leave it. - Before each B-refining macro-cycle the overall isotropic B of the scale moves into the atoms and the solvent's B (F_model unchanged), so the two do not drift against each other. Tried and not kept: xyz and B as one L-BFGS vector (the B block scaled by its curvature, the positions by the median X-ray curvature): no better than alternation with a memory per block on 12 starts (mean R-free 0.265 vs 0.262), worse on 7arr/7d98; a refit before each B step: no gain for +20-40% time. Refinement battery MD starts, median R-free by the REFMAC 0-cycle scorer, previous commit -> this (REFMAC to convergence): 5f6m x8 0.167 -> 0.167 (0.168), 8dqb x8 0.291 -> 0.294 (0.284), 7arr x4 0.270 -> 0.278 (0.311), 11if x4 0.245 -> 0.244 (0.251), 5reo x4 0.312 -> 0.258 (0.261: the ladder no longer keeps B held where B is the model's largest error), 7d98 x4 0.342 -> 0.335 (0.361). Deposited models: unchanged (B stays held there). Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit ed292f35b482b696d81f71f1d97e0016ca05b144)	2026-10-26 01:38:24 +01:00
leonarski_f	6369a263b1	Refinement: one trajectory of short weight trials instead of a ladder of full refinements from the start ... Every rung of the old ladders (6 positional, then 3 B) was a full 10-cycle refinement from the placed model, so ~90% of the evaluations were thrown away and the kept trajectory had 100 iterations. The run is now: 1. a ladder from the placed model, 2 macro-cycles per trial: three positional weights (w0/1024, /128, /16), each with the B factors held and refined (adp = 4 w), chosen by the old rule (tighter first, a later trial wins only within the geometry bounds and by more than the R-free tie); 2. a trajectory of steps from where the last one ended, each two trials side by side - the weights as they are and the X-ray term raised, in turn the positions' (x2, at most w0/8) and the B factors' (x4) - until a step lowers neither R-work nor R-free by more than the tie (at most 8 steps); 3. a final ladder from there at x1/2, x1, x2. A macro-cycle is 30 positional and 20 B iterations (the minimiser's memory kept within a trial). A trial starts from the scale, solvent and likelihood fit its predecessor ended with (the same computation, so result-neutral), and the slots that run share the threads. On 5 battery MD starts (start 1 of 5f6m 1.09 A, 8dqb 2.04, 7arr 0.92, 11if 1.37, 7d98 3.32; R-free by rugnux's scorer, REFMAC 0-cycle within 0.002), previous commit -> this, against REFMAC run to convergence (40-100 cycles): 5f6m 0.215 -> 0.167 (REFMAC 0.168), 8dqb 0.341 -> 0.290 (0.284), 7arr 0.356 -> 0.289 (0.288), 11if 0.295 -> 0.236 (0.244), 7d98 0.393 -> 0.337 (0.360). Time 5.4 / 8.6 / 7.3 / 3.9 / 10.0 s on the RTX 5080 (base 6-7 s). Halving a weight during the trajectory never won in the logs, so steps only try raising it; the final ladder can lower it. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit 2bfb84bc4f3c72e8da37e54b728839b65a636519)	2026-10-26 01:38:24 +01:00
leonarski_f	4424d8884d	Refinement: an own L-BFGS whose memory outlives the macro-cycle, B steps scaled by their curvature ... Each macro-cycle of a weight trial used to start a fresh Ceres solve: the L-BFGS memory was dropped every 10 (positions) or 5 (B) iterations and every cycle began with a steepest-descent step. RefinementMinimiser keeps one memory for the positions and one for the B factors across a trial's macro-cycles (the target's scale and likelihood parameters are refitted in between, which the memory tolerates), with a backtracking Armijo line search and Oren-Shanno scaling of a diagonal initial inverse Hessian. The diagonal: for B, the X-ray curvature per atom - the likelihood's curvature in |F_model| per resolution shell against the atom's (s^2/4)^2 f^2 exp(-B s^2/2), calibrated once per trial by a central-difference probe along a random direction - plus the B restraints'. For the positions none: tried with the restraints' Gauss-Newton diagonal (bonds and angles, ~1e4 per axis against the X-ray's ~1e2) it slowed the minimiser, since that stiffness is in directions that move bonded atoms together. Same budget (10 cycles x 10 + 5 iterations, same ladder), median R-free (REFMAC 0-cycle scorer) from the refinement battery's MD starts, base -> this: 5f6m (8 starts) 0.250 -> 0.210, 8dqb (8) 0.387 -> 0.345, 7arr 0.383 -> 0.356, 11if 0.325 -> 0.295, 5reo 0.316 -> 0.326 (CA RMSD 0.48 -> 0.43), 7d98 0.416 -> 0.393; REFMAC converged: 0.168 / 0.284 / 0.311 / 0.251 / 0.261 / 0.361. Deposited models (14 parity sets): R-work lower, R-free +0.0035 on average (their free sets were fitted to; the minimiser now moves the bottom rung further). Time unchanged. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit dfba4c1bd3c9345f31b64fd1cadc805810960825)	2026-10-26 01:38:24 +01:00
leonarski_f	626afc49dd	Refinement likelihood: the searches over D alone with the variance taken once ... EstimateLikelihoodParameters' golden-section searches over D at a fixed beta - four per bin on the free reflections, and the one on the working reflections the D/FOM change added, 50 evaluations over 95 % of the data - evaluated -ln L reading every row through the index and taking log(var) at every evaluation. The rows are now gathered per search with their variance and its logarithm; the sum is the same expressions in the same order, so D, beta and everything after are the same to the bit (refined model and report identical on the seven timing sets). refit.ml 200 -> 140 ms per cycle on the 1.1 A set, one thread per trial slot. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit 23ad3bfc254d10af310f17dbb8f85616f666a783)	2026-10-26 01:38:24 +01:00
leonarski_f	6075239be0	Refinement likelihood: D on the working set, the measurement error per component, as REFMAC 5.8 estimates them ... The likelihood's variance per bin (beta) is fitted by maximum likelihood on the free reflections as the whole spread of Fo about D Fc, and D is then fitted on the working reflections with the variance eps beta + 2 sigma^2 (acentric; + sigma^2 centric), which is also the target's variance. Murshudov et al. (2011) Acta D67 355: D from the working set, the variance from the free set. The measurement error is thereby counted twice, so D and the figure of merit fall where sigma is a large part of the spread - at high resolution. Measured on REFMAC 5.8.0431 0-cycle output (black box) of the 14 parity sets: its FOM inverted per reflection gives var = eps a + 2 sigma^2 (acentric, fitted coefficient 2.00) and eps a + sigma^2 (centric); its D (FC_ALL/FC_ALL_LS = the log's SigmaA_Fc1) and a are reproduced by this estimate (on REFMAC's own Fc, one set to rms 0.009 in D over all 20 bins). The previous per-bin free-set ML put D at 0.39-0.48 where REFMAC has 0.06-0.13 in the outermost bins. rugnux score vs REFMAC 0-cycle, 14 sets: mean |FOM difference| 0.056 -> 0.012 (max 0.112 -> 0.042), per-bin D rms 0.107 -> 0.068; R-work/R-free unchanged (D does not enter them). The score's FOM is now the mean over the working reflections, as REFMAC reports it, and the refined model's maps are weighted by the refinement's own m and D rather than a separate sigma_A estimate. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit d00d635e2874bff6cd216b7f24367362d0cc2e56) (cherry picked from commit b93e0ea2fc1ffcc6bb40dae9b77816a321f4d6ec)	2026-10-26 01:38:24 +01:00
leonarski_f	bcb71136ab	Refinement restraints: metal ions bound to their donors by the model's LINK records ... Metal sites were held only by the 1.9 A metal contact of the repulsions; REFMAC restrains the metal LINKs of the coordinate file (its documentation), which was the one geometry term the 0-cycle comparison did not share (one 2.8 A set: bond rmsd 0.018 against REFMAC's 0.042). - monomers/metals.cif: the Monomer Library's own statistics of metal sites (metals.json, LGPL data as the rest of monomers/), cut by update_monomers.py to the metal ions of its compound list and O, N, S donors: mean distance, spread and number of sites per metal, donor element and coordination number. - AddMetalLinks (before prepare_topology): every LINK / struct_conn record between a metal ion and an O, N or S that no link of the dictionary describes (its ZN-CYS, ZN-HIS, FE-CYS, FE-HIS are taken as they are) gets a link of one bond at EmbeddedMetalDistance for the two elements and the ion's coordination - the number of its donor records, symmetry mates included - from the rows resting on at least 20 sites (the coordination's own row, else the neighbours interpolated), sigma their spread (>= 0.02 A); a His or Cys donor loses the proton the bond replaces (DEL-HD1 / DEL-HE2 / CYSmod1, as the library's links do). Records only, no distance search; records to a symmetry mate count for the coordination but are not restrained (bonds to symmetry mates are not, anywhere). - The metal bonds are a restraint set of their own (RefinementTopology::metal_bonds), evaluated with the geometry and reported apart (GeometryStatistics::rmsd_metal, REFINE_RMSD_METAL_BONDS, REFINE_SCORE_RMSD_METAL_BONDS / _BONDS_ALL): their sigma is the spread of real sites, so they sit further from ideal than covalent bonds, and the weight ladder's 0.02 A bound stays a bound on the covalent ones. refine_parity.py compares REFMAC's bond rmsd (links included) with the combined one, and takes --gpu. Score-only geometry against REFMAC 5.8 0-cycle, all bonds (count): 2.8 A Zn/Fe set 0.0402 (4934) vs 0.042 (4935), was 0.0178; a Zn-Cys set 0.0186 (7102) vs 0.019 (7102); a Ca set 0.0297 vs 0.026 (REFMAC also refines the sugars and uses one Ca-O distance); a Mg set 0.0114 vs 0.017 (REFMAC restrains 8 symmetry links and puts Mg-O at 1.99 A, the library's statistics at 2.07). R of the scored model unchanged (+0.0001 on the first from the removed His/Cys protons). Refined R-free with the links vs without: +0.0016, -0.0002, +0.0005, +0.0004. Test: RefinementRestraints_metal_links (Zn-Cys4 by the dictionary's link, Mg(H2O)6 by the new ones, both back at their distances). Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit 0fcffc5c71e03e184cff18f07524473462a57b68)	2026-10-26 01:38:24 +01:00
leonarski_f	9da3851844	Refinement: at most n weight trials at a time, and a cancel flag the caller can set ... - RefinementSettings::max_trials_at_once (rugnux_refine_test --trials-at-once): 0 as many as the ladders and the cards take, 1 one after another - the check that side by side changes nothing. Verified: refined model and report identical, side by side vs one after another, GPU (5reo, 9yl4, 6o2h, 9rcs) and CPU engine (6o2h, 9rcs, 5reo), and run to run. - RefinementSettings::cancel, an atomic flag for the broker's live deadline: checked at every iteration of the L-BFGS (positions, B, rigid bodies, group B: the minimiser stops where it stands), at every macro-cycle and before every weight trial. The trials that ran are chosen among as usual; cut before the first, the model is the placement's. RefinementResult::cancelled says so. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit f708d3d227bb42215ffe3d9a15c766dbd73b783c)	2026-10-26 01:38:24 +01:00
leonarski_f	8718065a7c	Refinement GPU: the bulk-solvent mask on its own fine grid on the card ... The score draws the mask on a grid of its own (min(d_min/3, 0.4 A), BulkSolventMask) on the host; on a GPU engine that was a CPU mask and transform every cycle, per trial slot on one thread. Now the engine masks on that grid itself: - RefinementGPUSetup::mask_grid (BulkSolventMask::MaskGrid, the grid the host mask uses); where it is not the structure factors' grid the engine reserves a grid, a spectrum and an R2C plan for it (counted in DeviceBytes and the FFT work area), and Fmask masks (ModelMaskGPU), transforms and reads the rows there. Refit takes the engine's Fmask on a GPU, BulkSolventMask on the CPU. - ModelMaskGPU's shrink: each edge point marks its stencil as solvent instead of every macromolecule point searching its stencil for an edge - the same idempotent stores to the same points, so the same mask to the bit (ModelMaskGPU_* tests unchanged), and a thin shell of points visited instead of half the grid. - BulkSolventMask finds its symmetry orbits at its first mask: a GPU refinement never draws one on the host (1.1 s of trial-slot setup on the 3.6 A set). The card's mask is gemmi's but at points exactly on an atom's radius (ModelMaskGPU.h): R-work/R-free of the 14 parity sets on the GPU are the CPU engine's to 4 digits. Refinement deterministic run to run on the GPU (7 timing sets, refined model and report identical over 5 runs of successive builds that did not change results). Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit 89b5d00907c9ad99e8b389f6272a3724f981cd10)	2026-10-26 01:38:24 +01:00
leonarski_f	46ad2c10ed	Refinement GPU: the robust scale fit on the card, the pool back in every trial slot ... The score's robust fine pass (pseudo-Huber IRLS of ModelScaleBox::robust) on the device, so that refinement on a GPU no longer fits its scale on the host every cycle - with the trials side by side that was a robust grid search on one thread per slot (13-133 s per refinement on the seven timing sets, against 1.7-8 s before the score commit). - ModelScaleGPU: the weights multiply the WSSR and J^T J / J^T r in scale_sums (a weight row per fit, reserved at the first robust fit); robust_residuals / robust_weights kernels; the median of each fit's first residuals taken on the host as FitModelScale takes it (nth_element at n/2, on the fits' threads); LevMarBatch split out of FitBatch so that the rounds restart from where a fit stands. FitSolvent(..., robust) refits the coarse winner in the fine pass, as FitModelScale's robust fit does; the plain fit is unchanged. - ModelScaleGPUPool::Fit(..., robust); its streams at the highest priority: a fit is a chain of small launches the host waits on, and on a card shared with the trials' long kernels each wait queued behind them (refit.scale 58-87 ms -> 14-45 ms per cycle, the result the same to the bit). - Refinement: the main context and every trial slot fit on their pool (robust); the CPU engine keeps FitModelScale's robust fit. The card's fit is FitModelScale's to rounding (float residuals and weights, the steps' anisotropic factor in float), deterministic run to run and whichever engine a fit takes: R-work/R-free of the 14 parity sets on the GPU equal the CPU engine's to 4 digits (largest difference 1.4e-6 on the 3.6 A set). Test: ModelScaleGPUPool_RobustMatchesFitModelScale (one reflection in fifty a 4x outlier, five cells). Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit d15f048cbd7ed2d6b430f9f9cb5018ca284da8f0)	2026-10-26 01:38:24 +01:00
leonarski_f	a218c0bec8	rugnux --mode refine: refine a model against merged structure factors, nothing processed ... rugnux --mode refine --model model.cif -o out data.mtz The input is an MTZ or a structure-factor mmCIF, gzipped or not, by content (writer/RugnuxReflectionFile: parsing in the file layer, the library reads no file). Columns are found, not named: F/SIGF-like amplitudes (calculated amplitudes and map coefficients passed over), else intensities made into amplitudes by French-Wilson, else the mean of the anomalous pairs; the free set from a FreeR_flag-like column (0 the test set, or the minority value), else rugnux's own 5 % set. RunRefineOnly (rugnux/RugnuxRefine) runs RefineModel; the outputs are --refine's (_refined_model.cif, _refined_maps.mtz, _blobs.json) and a report with the REFINE_ keys, the input's REFINE_FRENCH_WILSON / REFINE_FREE_FLAGS, and every term of the start score under REFINE_SCORE_ (also in --refine's section). --refine-score-only scores the model as given; --refine-d-min cuts the resolution. tools/battery/refine_parity.py runs REFMAC 5.8 at 0 cycles and rugnux --refine-score-only on the same files and prints the terms side by side, with R by resolution from both programs' model amplitudes on the same reflections. Tests: [refine_only] - column choice (observed over map coefficients, intensities, 1-marks-free flags, no flags, no usable column), an MTZ read from its bytes, and the mode end to end on a synthetic cell (French-Wilson, generated flags, score-only, the report keys). Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit 63ee830c39c988588cffb8c9d4638a678815ec2c) (cherry picked from commit d7397311e6ce0d3bb37ac91e8973b6052e38589f)	2026-10-26 01:38:24 +01:00
leonarski_f	c4d2d419ce	Refinement score: the model's structure factors as REFMAC 5.8 scores them at 0 cycles ... Three terms of the score of a model - the same F_model at every stage, the as-given start and the refined end alike - and a breakdown of it: - Riding hydrogens from the start: the dictionary's hydrogens are added before the model is first scored (REFMAC's 0-cycle restores them; they move R by 0.010-0.013 at 1.1 A). The engine is made once, with them. - The bulk-solvent mask on a grid of its own, min(d_min/3, 0.4 A), at most 2^26 points. On the density grid (1.1 A at 3.3 A) gemmi's 0.8 A shrink found no grid offset and was skipped, which put R 0.015-0.03 high at >= 2.5 A. 0.3 and 0.4 A agree to 0.001. - The overall scale and anisotropic B by robust least squares (pseudo-Huber, iteratively reweighted, c = median |residual|) in the fine pass of the k_sol/b_sol grid (ModelScaleBox::robust, refinement only; MR and validation keep the plain fit). Plain least squares on |F| is the exact LS optimum but lets a few badly-fitted strong reflections set the scale (1.1 A set: R 0.1706 against REFMAC's 0.1600). The scale fit of refinement now runs on the CPU (no ModelScaleGPUPool). RefinementSettings::score_only scores the model as given and stops; RefinementResult::score_start carries every term (k, B, anisotropic B, k_sol, b_sol, mask spacing, R in 20 shells, -lnL work/free, the likelihood FOM, hydrogens; per-reflection terms with score_only). GeometryStatistics gains rmsZ. rugnux_refine_test: --score-only, --dump. Measured against REFMAC 5.8.0431 ncyc 0 (refi bref iso) on the same model, data and flags, 14 open-arm sets 1.1-3.6 A: R-work/R-free within 0.002 on 12 (was +0.003..+0.03); 7n2s and 9yl4 score 0.003/0.005 below REFMAC, which a 0.6-0.8 A mask grid reproduces. REFMAC with ANISOU stripped scores identically, so isotropic B is not a parity term. Open: the likelihood's D/FOM (ours 0.01-0.11 higher at high resolution); geometry differs only by REFMAC's metal LINK restraints and residues outside the embedded dictionary. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit 4f94b21611874ad9dcf89e6771fe311a0e10bb06) (cherry picked from commit 00db6a6f539ac2da515c0a649474335f4c4b07b8)	2026-10-26 01:38:23 +01:00
leonarski_f	8933a72a89	Refinement: the weight trials side by side, each on a model, topology and engine of its own ... Every rung of the weight ladder starts from the same model and depends on no other, so the six position trials, and then the three B trials at the chosen weight, run at the same time: on the main model and engine and on up to five slots beside it, each a copy of the model before the topology was made (the topology is built again on it, hydrogens included) with its own engine. The slots go on the GPUs in turn from the main engine's, as many as each card's budget takes, so a machine with several cards spreads them; a slot whose engine cannot be made is left out, and with none the trials run one after another on the main engine as before. The threads are shared out among the slots. The log lines and the choice are made afterwards in ladder order, so the log, the trial table and the refined model are the same, bit for bit (GPU and CPU engines checked). 5reo 3.9 -> 2.5 s, 9yl4 13.4 -> 7.8 s, 6o2h 3.1 -> 1.9 s, 8dyz 4.6 -> 2.7 s, 9rcs 2.9 -> 2.2 s (one RTX 5080, -N 8). Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit 0ea6a6db8aba640afc5249fe748922ddfaa2537a) (cherry picked from commit 0c0176c8bf571ed26f8a68a9de40222487c6200e)	2026-10-26 01:38:23 +01:00
leonarski_f	5569f3d1f2	Refinement GPU: the X-ray target and the restraints in one submission with one wait ... RefinementEngine::EvaluateWithRestraints evaluates both targets at the model's atoms. On the GPU the X-ray chain is queued first, the restraints' coordinates are written into a pinned buffer while the device works on it, the restraint kernels follow on the same stream, and the host waits once; the sums and gradients come back through pinned buffers. Same kernels on the same inputs, same bits. The CPU engine keeps calling the two in turn. 9yl4: evaluation 5.1 -> 4.7 ms, refinement 14.2 -> 13.4 s; 5reo 4.0 -> 3.9 s (RTX 5080, -N 8). Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit 51434b98b62a9e6322ffe811bf272a45ff6ce003) (cherry picked from commit 0bcfa3f8041cec4bb4bc376b8559f30c36d3ac80)	2026-10-26 01:38:23 +01:00
leonarski_f	001e61c1a4	Refinement: the repulsion search on the refinement's threads, hydrogens skipped before the neighbour walk ... BuildRepulsions walked the neighbours of every atom and only then dropped the pairs of a riding hydrogen; those atoms are now skipped before the walk. The atoms are searched in 64 blocks under ParallelFor and the blocks' pairs joined in atom order, so the restraint list is the same as before for any thread count. The model is no longer copied for the NeighborSearch. Same bits. 9yl4: repulsions 3.37 -> 1.09 s (91 calls), refinement 17.7 -> 14.2 s; 5reo 0.38 -> 0.12 s (RTX 5080, -N 8, loaded box). Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit ded11388a18f5a4138a73150c4bb073570152727) (cherry picked from commit 9c96836a90c9f170008d343af2cd885a4e59b321)	2026-10-26 01:38:23 +01:00
leonarski_f	e3782cabe4	Refinement GPU: atom densities uploaded only when some B moved, one device copy, positions through a pinned buffer ... Every evaluation uploaded both copies of the atoms' densities (the gather's and the gradient's) and their boxes, although in a positions-only minimisation no B changes between two Refits. The engine now keeps one copy (the gradient kernel reads ModelDensityGPU's atoms and boxes), uploads it only where some atom's density was made again, and sends the positions from a pinned buffer without waiting. The densities that are made again (every atom in a B minimisation) and the grid positions are worked out on the refinement's threads. Same bits. 9yl4: upload 3.29 -> 0.56 s, host side 1.29 -> 0.61 s, refinement 22.3 -> 17.7 s; 5reo 4.8 -> 4.4 s (RTX 5080, -N 8, loaded box). Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit 46c3b67c91aee0aec3473b0fb1a4945c00bda070) (cherry picked from commit 0aebc98110c8155932af647d6204891aec662294)	2026-10-26 01:38:22 +01:00
leonarski_f	dd49d4e2f2	Refinement: the likelihood's D and beta fitted bin by bin on the refinement's threads ... EstimateLikelihoodParameters fits each resolution bin on its own and writes only that bin's values, so the bins run under ParallelFor; the result is the same, bit for bit. It was the largest single stage of a refinement (107 calls, one core): 5reo 2.42 -> 0.56 s, 8dyz 2.46 -> 0.57 s, 9yl4 3.54 -> 0.88 s; whole refinement 5reo 6.3 -> 4.8 s, 8dyz 6.9 -> 5.3 s (RTX 5080, -N 8, loaded box). Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit 85aa34d3031c8e36be4462fca544bc801af45d5a) (cherry picked from commit d84ba55252adf455d5b4ba62052dfbafa6290a64)	2026-10-26 01:38:22 +01:00
leonarski_f	24b1711d64	Refinement: time per stage - an NVTX range per call and one TIMING line per stage with its sum and calls ... RefinementStage sums the time of each stage over a refinement (Refit and its parts, the evaluations and their X-ray, restraint, host and upload shares, the repulsion build, the riding hydrogens, the rungs) and logs it at debug level at the end; rugnux_refine_test -v shows it. No change to any result. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit 9491f54e0beccf36c65ebcec9afff90d08485f86) (cherry picked from commit 0ce206a88df960754476ce2f75ffaed90fbf3123)	2026-10-26 01:38:22 +01:00
leonarski_f	07ae590e54	Serial stills: the indexing ambiguity resolved from the data when no reference or model is given ... Where the space group is given (-S) and its lattice admits alternative indexings, a stills run without -z or --model used to merge the crystals' random indexings together (and warned). The crystals are now made consistent with each other before anything is scaled (ReferenceFreeReindex): each takes the indexing in which it agrees best with all the others (Brehm & Diederichs 2014), agreement being the sum over shared reflections of the products of shell-normalised, per-crystal standardised intensities, weighted by 1/(1+(sigma/sd)^2). The sum over all pairs is (|M|^2 - const)/2 for M the running sum, so a pass over the crystals is one pass over the reflections rather than over all pairs: coordinate ascent, four seeded starts, stop when <= 1 crystal in 1000 moves, the overall relabel that moves the fewest crystals. Deterministic (fixed summation order, sequential passes). A twin law of a pseudo-merohedral cell whose axes differ by a few per cent is decided by the crystals' own refined cells, which the indexer has already used: where >= 90% of the crystals' cells fit better as indexed, those crystals are anchors and only the others are decided by the intensities. Without this, two public sets got worse (pal90 R-free 0.183 -> 0.207, lcls242_t 0.296 -> 0.350). With a reference or model the per-image choice stands; the same resolution runs as a check, reported as AMBIGUITY_DATA_DISAGREES. New report keys (section 2): INDEXING_AMBIGUITY_RESOLVED, AMBIGUITY_CRYSTALS, AMBIGUITY_REINDEXED, AMBIGUITY_SEPARATION_SIGMA, AMBIGUITY_DECIDED_FRACTION (+ AMBIGUITY_TIME_S, dev). --mode scale is not changed. Still battery, no --model (R-free, REFMAC 0-cycle against the deposited model; before -> after; with --model for comparison): euxfel83 0.321 -> 0.207 (0.204), euxfel152 0.346 -> 0.257 (0.245), alvra213 0.209 -> 0.201 (0.207), alvra213_int16 0.210 -> 0.202 (0.208), pal90 0.183 -> 0.183 (0.188), lcls242_t 0.296 -> 0.294 (0.285); controls sacla237 / lcls222 unchanged (no ambiguity, no-op). The step takes 0.2-1.6 s on 2.7k-54k crystals; synthetic 64k crystals x 200 reflections 0.5 s. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit 80d378a1fe92364fd5b99a17f5c9ee8498412d36)	2026-10-25 23:26:32 +01:00