During a collection every dataset tick ran JFJochViewerDatasetInfo::UpdateLabels(), which
clear()ed the plot-type combo and re-added every item, so an open dropdown lost its hovered
row and scroll position on each tick and picking a plot type was a race against the next
update. The same clear-and-refill ran per tick or per image in the calibration window's
calibration combo, the ROI list combo and the powder calibrant combo; the last two also
threw away the user's choice (the calibrant was reset to the first entry on every image).
New LiveComboBox::SetItems() takes the full item list and leaves the combo untouched when the
list is unchanged. When it does change while the popup is open, the change is held back and
applied (queued) once the popup window hides, so a click that closes the popup lands first.
A replacement keeps the selection by item data, blocks signals, and a held-back one emits
itemsReplaced() so the owner can re-plot.
The calibration window now re-shows the selected calibration on a dataset tick instead of
always reloading the pixel mask over it.
Tested offscreen: a timer fires datasetLoaded() every 25 ms while the dropdown is open; the
popup and hovered row survive, newly available indexing metrics are held back until the popup
closes, and the picked type sticks and is what the chart plots. The rc175 code fails the
hover checks of the same harness.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
The Files panel never showed files written after a directory was first
listed when they came from another host (a detector writer on NFS/GPFS/
Lustre), because QFileSystemModel only learns about changes through its
inotify watching, and there was no way to refresh it by hand.
F5 (window-wide, only while the panel is visible) and a refresh button
next to the root's browse button re-list the root and every expanded
directory. A timer does the same every 3 s while the panel is visible
and no mouse button is held, but re-lists only directories whose mtime
changed since the last listing, so a steady tick costs one stat per
expanded directory.
QFileSystemModel has no rescan call; index() of a path it does not know
adds that row in place, so only the names missing from the model are
passed (index() is ~10 us a call; a CBF sweep is thousands of files).
Selection and expansion are untouched, new rows are sorted into place,
and the first visible row is kept where it was when rows land above it.
Entries deleted by another host still stay listed; local deletes are
seen by the model's own watching as before.
Measured offscreen on a 5000-file directory: unchanged tick ~1 ms,
re-listing the changed 5000-file directory ~5 ms.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
The mapping is now built while the frames are read, and with every core it took them from the
readers - on a 16M EIGER the read went from 0.10 to 0.19 s. Built on AvailableCpus() minus the
readers it is back at 0.11 s. The mapping is per pixel, so the same whatever thread count builds it.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01EizBKhTqrAYago9KJG3dA3
The null a placement must beat turned the whole assembly about its common
centroid, so with several copies it also moved them off the arrangement the
search found. Under tNCS, two parallel copies a tNCS vector apart fit the data
whatever the model is, and the null threw that fit away: wrong deposited models
reached TF Z 14-47 and 8-34 sd over the null on tNCS crystals, and two of them
decided the space group (SPACE_GROUP, a reflection file in the wrong group).
Each copy is now turned about its own centroid, all by the same rotation, so
only the model's own orientation is random. On a control of 38 open-arm sets
(deposited chain randomly re-oriented as search model, 3 unrelated deposited
models and a fold-scrambled decoy per set) the wrong models' null falls to
1.4-4.2 sd on the tNCS sets (one at 7.2, left UNDECIDED), both wrong decisions
become NOT_PLACED, and no right-model or AlphaFold-model decision changes
(nulls stay 15-107 sd). The 193-set AF survey replay loses no GREEN (two
UNDECIDED become NOT_PLACED); the four twin/tNCS targets stay correct.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01EizBKhTqrAYago9KJG3dA3
The spot-width stage of the pre-scan copied every preprocessed frame back to the host (72 MB a
frame on a 16M detector, page-locked host mirrors per worker) for measurements that read a few
pixels about each spot. Now:
- MeasureSpotsOnTiles: the flux curves and the footprint read (2*24+1)^2 squares about each spot,
gathered on the card (ImagePreprocessorBufferGPU::GatherTiles) - no copy_image_to_host, no host
mirror. The flux curves are bounded at R_BKG_OUT = 20 px. The footprint keeps its arithmetic; a
per-iteration check that its window is inside the square, and a spot whose window walks off it is
measured again from scratch on an 80 px square, then on the whole frame. Where the squares would
be more pixels than the frame, the frame is read. Same pixels in the same order, so the same bits.
Harness over 34 rotation sets (~1500 frames): 0 differences; misses at 24 on a few spots of most
frames, at 54 on up to 80% of frames of a few sets, at 80 on none.
- The azimuthal mapping and the per-worker spot engines are built while the frames are read.
- The tiers no longer wait for each other: workers run on through the visit order, each tier's
answer is drawn from exactly its own frames, and frames measured past the tier the answer stops
at are thrown away - a frame is measured the same whichever tier it is read for.
- PreScanMemo keeps the spot measurement, the defective pixels and the background gain under the
pre-scan key plus the spot-finding and azimuthal settings, so a copy of the run that pre-scans
again on the same inputs reads no frames.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01EizBKhTqrAYago9KJG3dA3
For every open-arm set where rugnux and the deposition differ in symmetry (sym_over, sym_screw,
screw_undetermined, accepted alternatives) and the sets the twin review flagged, an independent
assessment by established programs is now kept beside the manifest in
tools/battery/symmetry/<id>/: a summary.md and the trimmed POINTLESS and ZANUDA logs. Each row
names its directory in "symmetry_evidence". Nothing reads this for scoring, and no accepted or
rejected answer changes.
symmetry_evidence.py makes the evidence for one set. It re-runs the battery run's binary with the
unmerged export (p.hkl must equal the run's) and runs POINTLESS on the observations. It merges
them with AIMLESS in the deposited group and the model's setting, then runs ZANUDA with the
deposited model on three free sets, each chosen per lattice-holohedry orbit. It runs POINTLESS and
ZANUDA again on the depositor's structure factors, and tabulates the axial reflections of both
data sets for screw questions. ZANUDA's preference can move with the free set (6toc), which is why
there are three.
What the programs found, reported neutrally: an exact pseudo-symmetry, a twin or another effect
can produce any of these results, and the aim is only which answers the battery accepts.
6oww: ZANUDA prefers P 43 21 2 to P 21 on all four data sets, with lower R-free. 6toc and 8xtg:
ZANUDA prefers the higher group, but R-free is mixed (6toc) or favours the deposited group
(8xtg). 6pxb and 8xte: ZANUDA keeps the deposited P 32, and the deposited model in the higher
group refines far worse. 3r6o, 4bwl, 2wnq, 8c3e: the deposited model gives the higher group no
support. 5ebi: ZANUDA cannot reproduce the deposited fit. Screw sets: see each summary.
Run on rc175 fcbe920 battery run 20261012-0139 with CCP4 9.0.014 (POINTLESS 1.14.2, AIMLESS
0.8.2, ZANUDA 1.097 / REFMAC 5.8.0431).
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01EizBKhTqrAYago9KJG3dA3
- Likelihood (Read 2001; Z-score over random positions as McCoy et al. 2005): log-likelihood gain of
Rice/Woolfson E distributions, sigma_A from the pLDDT coordinate error with its scale refined, to
2.5 A (or the 20000 lowest-resolution reflections). Further-copy TF peaks ranked by the gain on the
search's reflections (peaks that lower it dropped); a copy whose TF Z is below 8 also stands out where
its refined likelihood Z-score reaches 8 - only where the copies placed are as many as Matthews makes
most likely. The likelihood is computed only where a translation function does not stand out.
Copy structure factors exact from one FFT of the cell's grid, or read off the molecular transform
where it reaches the likelihood's resolution.
- PAE domains: the AlphaFold DB's predicted_aligned_error JSON beside the model (same name pattern) is
read automatically; average linkage on the symmetrised PAE (10 A, domains >= 40 residues). Where the
whole model is placed nowhere, each domain is searched by itself side by side; placed domains must
agree, and a domain alone may only confirm the answer's group.
- Twin comparison: where the answer's merge chose and the twin hypothesis' merge exists, the chosen
placement read as a crystal in the subgroup (its symmetry images as copies, the subgroup's setting
found from the two cells) against the model searched for afresh in the subgroup, both against the
data twinned by the law (fraction refined on the working set, Yeates 1997); the subgroup is taken by
a 0.03 R-free lead plus its own null/margin -> TWIN_SUBGROUP, written to p_mr with law and fraction.
With --af-model rugnux makes the subgroup merge wherever a metric re-ask promoted the indexed group.
- tNCS rule: a group with fewer copies beside tNCS (screws bridged by the vector, or the enantiomorph)
no longer leaves the choice undecided where the chosen copies, carried into it and refined, fit
worse by 0.03 in R-free.
- Speed: the molecular transform's FFT on the GPU (cuFFT, serialised), no rigid body for trials that
lower the likelihood, re-search only with tNCS, PAE domains searched in parallel.
Survey (193 sets, MR replay on stored merges): single GREEN 58 -> 68, multi 48 -> 58, partial 8 -> 9;
4bwl (and, in full runs, 2wnq and a withdrawn entry of the same protein) TWIN_SUBGROUP P21 instead of
a wrong AGREES; a P21212 set with tNCS now SPACE_GROUP P21212 instead of UNDECIDED; no wrong call.
CPU and GPU builds make the same decisions on 18 demo/multi-copy/twin sets.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01EizBKhTqrAYago9KJG3dA3
Both run on the same runner machine and its one GPU. In run 380387 the unit-test job reached
Rugnux_FirstPassMemoMatchesRecomputation while the battery job (same runner, same minute) was
processing one of its larger sets; the FFT indexer's cuFFT plan found 0.1 of 15.6 GB free and the
test failed, as a GPU out-of-memory is meant to. The unit-test job joins the battery's concurrency
group, so the two no longer overlap (which also keeps the battery's timings clean).
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01EizBKhTqrAYago9KJG3dA3
A developer tool, not built or installed upstream. It also failed to link in both portable builds
(static cuFFT without the device-link step on Linux with CUDA, ws2_32 on Windows).
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01EizBKhTqrAYago9KJG3dA3
The group reduction reaches every observation through the group permutation, and so fetched one
32-byte sector per field for I, sigma, partiality and corr. I, sigma, partiality and prescaling_corr
now sit together in one aligned record, so it fetches two sectors per observation; the grouping
kernels' finiteness test and the combine read the same record. The per-observation fit coefficient,
its flag and 1/sigma are no longer stored: the per-frame fit forms them as it reads each observation
(the same expressions, so the same bits), which removes PrepScaleObsKernel and 13 bytes per
observation of device memory. DeviceBytes' per-observation figure drops by those 13 bytes.
Every sum keeps its order: p.hkl md5 identical to the base on cytc, 8a1a and 8qaw.
RTX 5080, nsys, merge-engine kernels: 8a1a 2459 -> 1924 ms, 8qaw 3624 -> 3025 ms, cytc 501 -> 476 ms
(ReduceGroupMeans 1.5-1.6x faster, PrepScaleObs gone, FitPerFrameG absorbs it).
Measured and not taken: storing all per-observation arrays in group order makes the reduction 3-4x
faster on its own, but the per-frame fit then has to gather, and moving 15 arrays at every grouping
costs as much as the reduction saves (net 0 on the 5080); a record for the combine-only fields
did not speed the combine.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01EizBKhTqrAYago9KJG3dA3
The budget is checked before the read, so a frame that will not be kept is read into the worker's
reused buffer instead of a fresh one paged in and let go (a 16 Mpx CBF sample kept 29 of 60 frames
and paged in all 60), and a kept frame borrows the worker's reader scratch for the read instead of
allocating one of its own. The budget can now be passed by at most a frame per worker.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01EizBKhTqrAYago9KJG3dA3
2ygz is a withdrawn PDB entry of the same protein as 2wnq, so it scores nothing that 2wnq does not.
6oww's deposited 8-chain P 1 21 1 model obeys the 4-fold and 2-fold the higher group adds, and its
|Fc|^2 correlate across the added 422 operators at 0.97-1.00, so P 41 21 2 is accepted beside the
deposited group - marked as an open question, as no refinement has compared the two.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
The beam-stop projection (ShadowAccumulatorGPU) and the defective-pixel sums (HotPixelFinderGPU) are
now kept one per card, fed by workers pinned t % gpus like the other pre-scan workers, and folded
into the first card when they are read (cudaMemcpyPeer + an integer add / max-with-count kernel).
All of them are integer sums or a maximum with the first-value rule, so the fold is order-free and
the result is identical to one card's. With one card nothing is folded.
The pre-scan sample is read once and kept (compressed as stored; up to 2 GiB, a frame past that is
read again where it is wanted) for the spot measurement and the defective pixels, which read every
frame again each before - a CBF/marCCD/SMV frame was decoded on the host three times.
A beam-stop detection that finds no shadow leaves the mask as it was, so every probe copy of the run
repeated it on the same inputs. Its answer (shadow, ring centre, mean projection) is now kept in a
memo shared with the copies, keyed on the sampled frames, the geometry the rings are drawn in, the
polarization and the binary mask; up to 4 entries.
Debug TIMING lines for the pre-scan's parts (read and projection, beam stop, defective pixels, spot
measurement). New tests: two accumulators/finders folded match one fed every frame.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01EizBKhTqrAYago9KJG3dA3
Copy number. The hard "Vm >= 4: MULTI_COPY, no decision" rule is gone. Copies
are searched one after another up to the largest copy number with a Matthews
probability of 1% (a Gumbel distribution with Kantardjieff & Rupp's 2003 mode
and mean, no resolution dependence); COPIES_LIKELY reports the most probable.
Sequential search. Copy n's translation function carries copies 1..n-1 as a
known partial structure: the cross term 2 Re(conj(F_known) F(t)) goes on the
same FFT grid (CPU FFTW and GPU cuFFT; KnownStructureFactors, AssemblyCorrelation).
Its peaks, past those that clash, are ranked by the correlation of the whole
assembly with E^2 (the TF itself, linear in |F|^2, rewards copying a placed
copy onto an origin shift), the first that stands out (TF Z >= 8), packs and
lowers R-free by 0.01 is kept; each copy is refined beside the others held
fixed (RefineRigidBody's fixed copies), and the first copy again beside the
second, the earlier ones once more at the end.
Packing: ClashFraction counts C-alpha clashes with other copies and all their
mates, binned (7mzt: 51 s of clash checks -> 1.9 s).
Search quality: rotation-function peaks hill-climbed off the 6 deg sampling
(6ze4: RF Z 10.4 -> 16.0, 3.3 deg off the deposited orientation -> 0.2); the
first copy goes down the TF list until three placements that pack are
refined, so a group is CLASH only where no offered orientation packs; groups
are searched side by side, and every group the best one leads is searched
again with the best one's copy orientations tried first, the better search kept.
tNCS: the native Patterson of E^2 (5-10 A) off the lattice; placed copies'
orientations join every further copy's search; and where the tNCS vector turns
one group's screw axes into another's (TncsRelatesGroups), a group whose search
stopped at fewer copies does not lose to the other - UNDECIDED. Measured on an
in-house tNCS crystal (vector c/3 along the 3-fold): both hands fit with three
copies to within 0.01 in R-free, and where one hand's search failed the other
was taken as ENANTIOMORPH; now UNDECIDED.
Null: the replicates are placed by the translation function in their own
orientation, as the search placed the real one (a null at the real centroid
reads high), and the gate is 4.51 = t(8) sqrt(1 + 1/9), 3 sd of a nine-draw
null, the gate --model's MODEL_FIT is now read at.
Speed: placements scored on the GPU structure-factor engines; further copies'
trials score with the first copy's bulk solvent held, the assembly refitted at
the end. Survey of 193 sets (jfjoch_mr_replay on stored merges, RTX 5080
shared with other jobs): MR median 1.15 s, max 24 s; demos 0.8-1.1 s.
Report: COPIES and COPIES_LIKELY columns, MODEL_PRIOR_COPIES.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01EizBKhTqrAYago9KJG3dA3
An optional `fixed` model: other atoms of the crystal held where they are -
the other copies of a molecular-replacement search - whose Fcalc is added to
the body's at every evaluation and whose atoms the bulk-solvent mask covers
together with the body's (computed once per zone, with the body where the
zone starts, and held). With them the origin is no longer free, so the gauge
projection is skipped. On the CPU the fixed part is gridded once per zone; on
the GPU the fixed atoms must be copies of the body, and each one's placement
is read off by Kabsch superposition and composed on the device with the
engine's own density, transform and mask (SetFixedCopies), so a fit beside
three copies of a 90 kDa model costs what a fit alone does.
Without `fixed` nothing changes (the composition kernel's extra term is null).
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01EizBKhTqrAYago9KJG3dA3
A run can make the same first pass several times - the canonical pass and the probes at the
geometry it stands at - and each of them that carried a near tie left its own re-check. The first
pass is deterministic in its inputs (FirstPassInputKey, the key the first-pass memo already trusts),
deciding late as deciding early, so a re-check whose pass read the same inputs (and the same
pre-pass flag) as an earlier one takes that one's outcome instead of running again.
Measured on 4p8r (8 re-checks, 5 on inputs of their own): re-checks 18.7 -> 13.5 s, p.hkl
identical. A diagnostic build that runs the skipped re-checks anyway and compares is used to
check the outcomes agree.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01EizBKhTqrAYago9KJG3dA3
The kept-results directories are named by the machine's role, not its host name:
tools/battery/results/workstation/<run>/ (1 socket, RTX 5080) and results/server/<run>/ (4 sockets,
4x T4). battery.py keep takes the role as --as; the kept files, untouched, still record the real
host and hardware. The server's rc175 full battery now has all three files (open + inhouse, private
false); checked for the private arm's set ids and input directories.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01EizBKhTqrAYago9KJG3dA3
Run directories are scratch, and the paper tooling needs the runs it draws from to outlive them.
battery.py keep RUN copies a run's report.md, results.json and manifest.json as written into
tools/battery/results/<host>/<run>/ (outside docs/, which Sphinx publishes), the host and run name
read from the report. Open and in-house runs only: a run its manifest marks private, whose report is
report_PRIVATE.md or says PRIVATE ARM, or with an arm or row outside those two, is refused. A run of
which only report.md exists is kept with what there is.
The CI job now keeps results.json and manifest.json beside report.md, in
/data/battery/ci_reports/<run>/ and in the artifact, so a run on either host leaves what keep needs.
paper_plots.py resolves a RUN by name among the kept runs after runs_root.
Kept: the rc175 full battery on mpc2898 (20261011-1440_57fef1_rc175-57fef1c-full, all three files)
and on mx-aare-test (20261011-1236_549939_1.0.0-rc.175, report.md only; the other two are to follow
from that host). Both checked for the private arm's set ids and input directories.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01EizBKhTqrAYago9KJG3dA3
The battery job ran the ci tier and the wrong-model null in one step with one exit status, so a red
job did not say which of the two failed. battery.py nullmodel runs the null on its own, in a run
directory whose report is just that section, and exits 1 when a pair failed; run --no-nullmodel keeps
it out of a --tier ci run. The workflow runs `run $SUBSET --no-nullmodel`, then (for a ci-tier run)
`nullmodel` as a separate step that runs whatever the first did, and keeps both reports. The ci tier's
own rows are unchanged; a plain `run --tier ci` still includes the null as before.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01EizBKhTqrAYago9KJG3dA3
Three defects the battery's wrong-model null found (5 sets x 5 deposited models of unrelated proteins):
CC(model, data) significance. The per-shell sigma was Fisher's transform on independent reflections,
but the data and a scaled model share the falloff across a shell, the anisotropic B fitted to these
very data, the bulk solvent and the symmetry enhancement epsilon - whatever the model is. 21 of 24
wrong models read CC_MODEL_CONFIRMED_TO_D_MIN to the data's d_min (10-15 sigma in most shells).
The correlation is now formed on I/epsilon and |F_model|^2/epsilon, and its null is empirical: the
data at h against the model at h + d for the 26 nearest lattice offsets, which keeps everything smooth
in reciprocal space and loses what the model knows of h. SIGMA = (z - mean) / max(sd, 1/sqrt(N-3)) in
Fisher z over those 26, a new CC_NULL column shows the null, and a shell confirms only beside a coarser
shell that also clears 3 sigma (one shell alone did so once in 216 wrong-model shells). Prototyped on
the p_maps.mtz of a full open-arm run and the null runs: wrong models confirm 0/24 (was 21/24), the
deposited models confirm 197/200 (was 198/200 in the prototype's reading; the one lost has CC_MODEL
0.05-0.13 in every shell). The report no longer says a model cannot agree by accident.
MODEL_FIT gate. Accepted at 3.0 sample sds of a nine-draw null, as if the sd were known; an unrelated
P1 helical model on a P3(1) helical crystal was ACCEPTED at +3.05. Against 48 draws it reads +2.09 and
the best random placement fits as well as it does, and drawing the null about the cell axes instead
changes nothing (+2.15): the cause is the nine-draw sd, not the orientation. The gate is now 3 sigma
allowing for that: t(8) * sqrt(1 + 1/9) = 4.51. The deposited models of the open arm read +7.0 and up.
The indexing lead stays at 3 sigma (INDEXING_MARGIN_SIGMA): it is read only behind the fit gate, and
a deposited model settles one at +4.15.
Rigid-body GPU reserve. The finest zone's observations were counted by the data's d, but the zones
count them by the d of the index in the model's ASU, and a model's group need not keep the data's
metric (an I2(1)3 model on I222 data: 2320 in the zone against 1712 reserved), so the validation died
with "zone over the engine's reserve". Counted the zones' way, under every indexing probed.
Tests: ModelValidation_CCModelUnrelatedModelConfirmsNothing (Fisher alone reads +4.7 on an unrelated
model with an anisotropic falloff; the new sigma stays under 1), ModelValidation_WrongModelInAGroupOffTheDataMetric
(fails with the old count), ResultReport_ModelValidationSection (CC_NULL column, lone-shell rule).
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01EizBKhTqrAYago9KJG3dA3
A developer utility, not installed: the search, the decision and the hand
check run on the answer's p.mtz (and the twin hypothesis' p_twin_<group>.mtz)
that a rugnux run wrote, so a survey of the search over every dataset with a
predicted model takes minutes instead of a reprocessing per set. The hand
check of an ENANTIOMORPH decision moves from the rugnux driver into
CheckEnantiomorphHand, which both call; unchanged.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01EizBKhTqrAYago9KJG3dA3
gemmi's table lists some groups a second time on another origin ("P 42 21 2a", "P 21212(a)",
"I 2 2 2a", "C 1 21 1"). SameRotationGroups kept them as separate candidates, so the true group tied
with itself in R-free and the choice came out UNDECIDED: five single-copy sets of the --af-model
survey (and one partial-model set) ended there. A group equal to one already listed up to an origin
shift on the twelfths is now left out.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
The ENANTIOMORPH hand check ran a whole ValidateAgainstModel on the placed model: model read and frame
probe, a rigid body, a 9-replicate null (~0.5 s of the ~0.6-0.9 s), sigma_A, three maps written. The
decision needs only --model's rule: the model fits its null (the MR choice has already required its
own null of the same construction) and the anomalous map at the model's atoms is not inverted.
ReadModelAnomalousMap (ModelValidation) computes F_calc and F_mask to the data's resolution (GPU engine
where there is one), carries them through the bulk solvent MR scored the placement with (the overall
scale and anisotropic B do not move phases), and reads the anomalous map with the same code as the
validation: its coefficient construction and its reading at the atoms are factored out of Validate
(anomalous_coefficients, read_anomalous_map) and used by both, so plain --model is unchanged.
Hand check 0.6/0.6/0.9 s -> 0.027/0.028/0.040 s on 11if/7ris/9zmu; same ADOPTED/VETOED on all seven
cases tried (the three demos, two anomalous lysozyme sets and their mirrored-detector runs), with the
scatterer means and deepest troughs within 0.1 sigma of the full validation's.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
- An MR ENANTIOMORPH decision is taken into the answer's label only as --model takes a model's
enantiomorph: ValidateAgainstModel runs on the placed model (in a scratch directory, removed after)
and its adopted_model_enantiomorph - fit over its null, anomalous map at the atoms not inverted -
decides; otherwise ENANTIOMORPH_VETOED. The hand-check numbers go to the MODEL PRIOR section.
- Rotation and translation functions on the GPU (MolecularReplacementGPU.cu): one block per
orientation for the rotation function; per orientation the copies, the bin weights, a gather of the
Crowther-Blow coefficients (CSR lists, fixed order, no atomics) and a cuFFT C2R, block-reduced
statistics finished on the host in a fixed order. The CPU path (FFTW) is unchanged in what it
computes; the orientation-independent part of the translation function (TranslationSetup) is now
built once per group on either path.
- Rescoring: a placement clashing with its mates over twice the limit is not refined, one rigid-body
engine per group, and the null is built only for the candidate the choice falls on.
Measured MR step on the RTX 5080 (before -> after, seconds; hand check extra where it runs):
3r6o 1.77 -> 0.67, neg 2.14 -> 0.37, 11if 1.20 -> 0.51 (+0.6 hand check), 7ris 1.46 -> 0.56 (+0.6),
9zmu 4.71 -> 1.07 (+0.9). Rotation 0.50 -> 0.02 s and translation 1.17 -> 0.13 s on 9zmu.
Mirrored-detector runs of two anomalous lysozyme sets: the hand check vetoes (map inverted at the
model's atoms); the unmirrored runs adopt.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
IndexerThreadPool_FFTIndexerWaitsForGPUWorkBeside filled only the test thread's
card, but an indexer worker takes its card round-robin (pin_gpu: a process-wide
counter modulo the device count). On the CI runner, a container given all of the
host's GPUs, the probe's worker could land on a card nobody had filled, build its
indexer and fail "CHECK(probe.Run(x, recip).error != nullptr)"; the two checks that
expect a wait passed there for the same wrong reason. On a one-card workstation the
worker is always on device 0, so it never showed.
Every card is now filled, each under its own device, and released the same way, and
the fill is topped up right before each Run so memory given back in between by
anything else does not let the indexer fit. The pools are trimmed on every card at
the end. What the test checks is unchanged.
Run 20x alone and with the [CUDAMemHelpers],[AdaptiveSpotFinderGPU] group, also with
another process holding 4 GB of the card: all pass.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
The pools' indexers return their memory to the allocation pool when destroyed; without a
trim the next GPU test in the same process (AdaptiveSpotFinderGPU_RunToRunReproducible)
found the card taken and failed with out of memory.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
The compiler's register choice held the fused decode/un-transpose/preprocess kernel to four
resident blocks per SM on the RTX 5080, where its shared buffer allows five. Asking for five
(48 registers, a small spill) takes it from ~391 to ~313 us per 18 Mpx frame (myob, -N 1, nsys,
repeated). sm_75 cannot hold five 256-thread blocks, so its code is unchanged (55 registers).
Output identical: ci tier base vs new, compare 0 changed, p.hkl identical on 26 sets, MTZ
reflection arrays identical on 49 files; [ImagePreprocessorGPU] passes.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01EizBKhTqrAYago9KJG3dA3
A predicted model (AlphaFold mmCIF, pLDDT in the B column) is trimmed at pLDDT 70, given B-factors
from the pLDDT (Oeffner et al. 2022) and placed by molecular replacement, one copy in the ASU:
- rotation function on a uniform 6 deg sampling of the point group's rotation ASU, each orientation
scored by the correlation of E^2 with the symmetry-summed |F|^2 read off the model's molecular
transform, computed once by FFT and interpolated (Navaza 1994);
- full-symmetry Crowther & Blow translation function (one FFT per orientation and group, through
MapFromFPhi/FFTW) for the 50 best orientations in every group with the merge's rotations;
- the best three placements per group through RefineRigidBody (GPU where there is one), bulk solvent
and R-free to 3 A, a C-alpha packing check against symmetry mates, Matthews, and the
random-orientation null for a placed candidate.
Decision: PLACED = TF Z >= 8, clash <= 5%, Vm in [1.5, 4), null >= 3 sd. Within the answer's merge
the placed group with the lowest R-free is chosen where it leads every other packing group by 0.03;
the twin hypothesis' merge is searched, and chosen, only where no group of the answer's merge can
hold the model at all (Matthews, packing). An enantiomorph relabels the answer as --model does;
another group goes to <prefix>_mr.mtz/.cif plus <prefix>_mr_model.pdb; the MODEL PRIOR report
section carries the table. The search runs on the CPU in both builds; without --af-model nothing
changes.
Measured (RTX 5080, MR step): 3r6o twin I41 chosen over I4122 (Matthews + clash) in 1.8 s, solution
0.09 A CA rmsd from Phaser's; 11if P41 -> P43 1.2 s; 7ris P3121 -> P3221 1.7 s; 9zmu P6122 -> P6522
4.7 s; 11if's model against 3r6o's data NOT_PLACED.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01EizBKhTqrAYago9KJG3dA3
