38 Commits

Include renames

Author	SHA1	Message	Date
leonarski_fandClaude Opus 5	59702b0123	spot_finding: give the ring reduction eight blocks per SM instead of four ... reduce_rings_shared is the largest kernel in the per-image loop - 73% of GPU kernel time on an 18 Mpx rotation run, launched three times per image - and it is bound by shared-memory atomic replay rather than by bandwidth: it reaches 156 GB/s against a measured 913 GB/s ceiling, and removing the atomics while keeping the same loads makes it five times faster. That is the case that wants resident warps to hide the serialisation, and four blocks per SM left only 512 of the 1536 threads an SM can hold. The per-block histogram is nbins * 20 B, about 9.6 kB at the default 0.01 1/A spacing, so eight blocks fit in shared memory with room to spare. Both kernels are grid-stride loops, so any grid is correct and a device that cannot co-schedule eight simply queues the rest. Measured: 9.21 s -> 5.33 s of kernel time over a run (852 -> 493 us per launch), cutting total kernel time from 12.57 s to about 8.85 s. flag_strong keeps four. It is bandwidth-shaped rather than atomic-bound and eight measured no better (181 vs 175 us). Wall clock is unchanged, and that is expected rather than disappointing: kernels are 39% of the image loop while the host-to-device copy is 78%, so faster kernels idle the GPU more without shortening the loop. This is groundwork for the transfer work, not a speedup on its own. The shared accumulators are float and summed with atomics, so the block count changes the summation order and with it the last bits. The 37-crystal battery is identical crystal for crystal except one observation in 925850 on a single dataset. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>	2026-08-03 00:02:34 +02:00
leonarski_fandClaude Opus 5	a047275760	spot_finding: fix the GPU finder's main loop, which the tests could not reach ... Two bugs in analyze_pixel, both confined to the middle stage of the wave. The kernel walks each wave's rows in three stages. The priming and drain loops read prev_out and substitute INT32_MAX for a pixel the previous pass found strong, exactly as the CPU finder's value_at() does on every read. The main loop did not - it read the image raw. So in the second pass the pixels the first pass found strong stayed in the background statistics, inflating the local mean and variance, and the halo of every broad spot failed the signal-to-noise test. The two engines therefore did not agree, despite 1a1e05ad1 having set out to make them. Separately, shared_sum2 is an int64 accumulator but val*val and old*old were computed in int32 at three sites. That wraps above 46340 while the detector overloads around 1e6, so any window containing a bright pixel got a corrupted variance. pixel_result already did the same arithmetic in 64 bits. The reason this survived is worth recording: numberOfWaves is fixed at 32, so a wave owns ceil(height/32) rows, and the main loop only runs while front < rmax with front starting NBX+1 = 16 rows ahead. At the existing test's 100 rows a wave owns 4 rows and THE MAIN LOOP NEVER EXECUTES - every row goes through priming or drain, and the parity test passed on the broken kernel. On a 4362-row detector frame a wave owns 137 rows and the main loop carries about 121 of them, so the bug covered roughly 88% of a real image. The new tall-image test is sized to the partitioning rather than to convenience: 1024 rows, spots placed inside the main-loop region, one core at 100000 to exercise the overflow. Against the unfixed kernel it reports GPU 25 pixels where the CPU finds 49 and fails six assertions. The default rugnux path is unaffected because it uses the adaptive finder, and the 37-crystal battery is identical crystal for crystal. The classic finder is what SpotFindingSettings defaults to, so this is the online receiver's path; measured there with --no-adaptive-spots, R-meas improves 11.2% -> 10.9% and CC1/2 98.8% -> 98.9% on one crystal, with multiplicity up on both tried. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>	2026-08-02 23:31:44 +02:00
leonarski_fandClaude Opus 5	8f1b0b2281	spot_finding: accumulate spot centroids in integers ... The photon-weighted position sums were floats, so the centroid's last bit depended on the build rather than on the data: gcc contracts the multiply-add in AddPixel into an FMA under -march=x86-64-v3 and cannot at the baseline, and MSVC does not contract at all under /fp:precise. The GPU extractor had to match with __fmaf_rn, and the parity test still needed a two-ulp slack for hosts that do not fuse. Column, line and the per-pixel count are all integral, so the sums are exact in int64 and both implementations reach the same bits with nothing to match. The parity test now demands exact equality unconditionally and gets it, including on a baseline build. ConvertToImageCoordinates keeps the sums integral too: the raw -> image map is a signed axis swap plus an integer translation, so it is applied to the sums instead of to the centroid. Drops the SpotToSave constructor, which had no callers and could not have been converted without quantising the stored centroid. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>	2026-08-02 19:03:35 +02:00
leonarski_fandClaude Opus 5	4bdb229fb8	spot_finding: find connected components on the GPU ... The spot finder flagged strong pixels on the device and then labelled them on the host, so every frame sent the packed bitmask back - 2.26 MB on a large detector - and the host walked all of it to recover a few hundred pixels. Do the labelling on the device instead: compact the bitmask into a flat-index-sorted list, find each pixel's backward neighbours by binary search, union them lock-free with path halving, then label, accumulate and filter in one kernel. Only the spot list comes back, and only one stream synchronisation per frame. The gain in the ordinary case is modest - about a quarter off per-image spot finding - because the host algorithm is genuinely fast on a normal frame. What justifies it is the frame that is not ordinary. The host labels a sorted sparse list through a window spanning two detector lines, so its cost is quadratic in how many strong pixels share a line. A lit band of detector rows - a hot module, a panel edge - costs 33 ms at two rows and 377 ms at fifteen, all of it under the pixel cap that was supposed to bound this, and none of it maskable when the cause is a diffraction ring rather than a defect: a ring runs tangent to a row at its top and bottom, which is exactly the shape that hurts. The device version is flat at 0.05 to 0.64 ms across every geometry tried, so an online run no longer stalls a quarter of a second on an ice ring. Rejecting an over-cap frame is now free too, since the count is known before any pixel is written. Also label once and filter three times. The per-image minimum-pixel search runs the extraction at three settings, but that setting only decides which components are kept - it does not change the components - so the search itself need not be repeated. This helps the host path as much as the device one. The resolution mask moves to the device as a bit mask, uploaded when the limits change rather than per frame, since the compaction needs it there. Parity is asserted permanently rather than argued: five cases covering realistic frames, occupancy from a hundred pixels to past the cap, the pathological geometries including rings, the resolution mask, and a hundred-repeat determinism check - requiring the same partition, the same spot order, and identical counts. The centroid is a float sum and therefore order-dependent, so the device walks each component from its root in ascending order and fuses its multiply-add the way the host's does; note that whether the host fuses at all depends on the architecture flags, so exact centroid equality is asserted where the compiler fuses and a two-ulp bound otherwise. Making those accumulators integer would remove that dependence entirely and is worth doing separately. Regression set: all 37 crystals identical to the last printed digit. Unit suite passes with the new cases. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>	2026-08-02 13:34:43 +02:00
leonarski_fandClaude Opus 5	6e805f53c0	image_analysis: stop paying for work that is thrown away ... Three independent costs, each measured, none changing a result. Across the 37-crystal regression set the run time halves (median per crystal 2.0x, total 2.3x) and every crystal's merge statistics are unchanged. The image copy back from the device moved the whole preprocessed frame - 72 MB on a large detector, every frame, per worker - to serve a single host consumer that reads only the strong pixels, at most a few hundred kilobytes of it. Give the buffer a Gather() so that consumer asks for the values it actually wants (a host loop on the CPU, a small kernel on the GPU), and copy the frame back only when a CPU spot finder will genuinely read it. The copy the other way was worse: it came from an unregistered vector, so the driver staged it through its own pinned pool with a host-side memcpy on the calling thread, which does not overlap and collapses under concurrency - 11.6 GB/s at one worker, 1.6 GB/s at eight. That, not any hardware limit, is why throughput stopped improving past four to eight workers. Pinning the decompression buffer once per worker fixes it: on a 18 Mpx dataset the image loop goes from 13.6 to 7.9 ms per image at 32 workers, and 32 workers now beat 8 instead of losing to them. Ceres was computing seventeen partial derivatives where five are free. The per-image rotation refinement frees the beam and the orientation and holds distance, detector angles, rotation axis and cell constant, but the cost function declared all seven blocks, so every residual evaluated in Jet<17> arithmetic. A residual exposing only the two free blocks - the same arithmetic, the constants baked in - halves refinement, and it is exact rather than merely close: dual coordinates evolve independently, so the residuals and the free Jacobian columns are unchanged bit for bit. The merge sorted an index array with a comparator that dereferenced a 1.6 GB array of 72-byte records, i.e. a random walk over memory, single-threaded, twice per two-pass run. Sorting a packed key instead is 2.4x. French-Wilson allocated its integration scratch per reflection and ran serially; it now takes caller-owned scratch and runs over chunks, 4.2x. The correction surfaces re-tested every observation for usability and parity on each of ~22 passes and re-allocated their accumulators each time; bucket the indices once and hoist the buffers. Also convert std::round to std::rint where the rounded value only ever enters a squared residual. The tie rules differ - away from zero against to even - so this is safe exactly where a tie flips the sign but not the magnitude, and unsafe wherever the value becomes a Miller index; those sites keep std::round. Verified over all 2^32 float bit patterns: 8388608 exact ties exist, and the squared residual is bitwise equal for every one of them. Worth little on its own here, because the rounding that dominates is in candidate refinement, where the value is an index and the substitution is not available. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>	2026-08-01 21:35:28 +02:00
leonarski_fandClaude Opus 5	0b1fb6c870	image_analysis: share the read-only GPU lookup tables per device ... One analysis engine is built per worker thread, and each uploaded its own copy of tables that are pure functions of the detector geometry: the pixel -> azimuthal bin map and the per-pixel corrections (both in AzIntEngineGPU AND again in AdaptiveSpotFinderGPU, from the same mapping), plus the pixel mask. On an 18 Mpx detector that is ~224 MB per worker; with 32 workers ~7 GB of device memory held 32 identical copies. Upload each table once per GPU instead and hand every engine on that device a shared pointer to it. The cache is keyed by (device, source-vector address) because workers are pinned round-robin across GPUs, so on a multi-GPU node each device keeps its own copy - a kernel may only read memory resident on the device it runs on - and the table is freed on the device that allocated it. Entries are held weakly, so a table goes away with the last engine using it. Measured on an 18 Mpx detector, 32 worker threads, 16 GB card: the stills path went from exhausting the card (OOM in de-novo indexing) to 8.6 GB peak, and a normal rotation run from 14.6 GB to 7.4 GB - it had been running within 1.6 GB of the limit, so any larger detector or second GPU consumer would have tipped it over. Per-worker footprint drops 403 -> 173 MB. Merge statistics are unchanged on a six-crystal regression subset, including two-pass runs where the second pass rebuilds the mapping on refined geometry, and wall time is unchanged (13.5-13.8 s vs 13.8-14.1 s). Also take the launch configuration from the current device rather than device 0 in AzIntEngineGPU and ImagePreprocessorGPU: with round-robin pinning, device 0's SM count and shared-memory size can belong to a different card than the one the kernels use. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>	2026-07-31 18:41:27 +02:00
leonarski_fandClaude Opus 5	1a1e05ad14	spot_finding: run the same two passes on the CPU as on the GPU ... ImageSpotFinderGPU::Detect launches its kernel twice, feeding the first pass's strong-pixel bitmap back in so the second recomputes each local background with those pixels excluded and keeps them strong. The CPU finder ran a single pass, so the two returned different spot lists for the same frame and a dataset processed without a GPU did not match one processed with it. It matters for any spot wide enough to reach into its own 31x31 background box: the spot inflates the mean and variance it is then tested against, so its outer pixels fail the SNR test. On the test image added here - a 5x5 core at 300 counts with a one-pixel ring at 25 - a single pass returns the 25-pixel core and 7500 counts where two passes return the full 49 pixels and 8100. pxl_val also becomes int64_t, matching the GPU's pixel_result signature. It was int32_t, so pxl_val * pxl_val overflowed above 46341 counts even though the surrounding sums were already 64-bit. The new parity test compares PixelCount and Count, not just the centroid, which does not move for a symmetric spot whether or not the ring was picked up; it was confirmed to fail against the old single-pass CPU. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>	2026-07-31 15:37:22 +02:00
leonarski_fandClaude Opus 5	d2d1d78545	spot_finding: keep the GPU wave inside the image ... rowsPerWave is rounded up, so with 32 waves the last waves can start at or past the last row: rmin was never clamped and only the drain loop checked front against height. On any detector below about 1500 rows - including the module-converted 500K and 1M geometries and the kernel's own unit tests - the priming and steady-state loops read whole rows past the end of the image buffer, and those garbage rows entered the sliding background window of the bottom rows. Blocks with no rows to write now return before the first __syncthreads (rmin depends only on blockIdx.y, so the block leaves together and the collective ops stay well formed), and both remaining reads are bounded by height. Rows past the end keep the INT32_MIN sentinel, which the window already treats as "not counted". The raw read in the steady-state loop is left as it is: making it apply the prev_out substitution that the other two read sites use would change which pixels are found, which is a separate question from this fix. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>	2026-07-31 14:43:49 +02:00
leonarski_fandClaude Opus 5	953302a9eb	Spot plot: the resolution axis comes from the detector, not from 1.5 A ... Dropping the fixed spot-finding limit left the reader still generating the spot-vs-resolution plot over shells that stop at 1.5 A, so a stored file reopened in the viewer showed a plot truncated at exactly the limit that was removed - GenerateSpotPlot drops every spot outside its shells. Pass the detector's own maximum resolution, as SpotAnalyze already does. That value is 0 when the geometry gives no scattering angle at all (no distance or no wavelength), and ResolutionShells throws on a non-positive d_min, once per image. There is no resolution axis to plot against in that case, so skip the plot. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>	2026-07-31 11:51:22 +02:00
leonarski_fandClaude Opus 5	bf866a0d4c	CUDA: the engines' setup copies belong on the engine's stream ... Making the worker streams non-blocking removed the implicit ordering that the constructors were still relying on. Each engine uploads its static inputs - the pixel mask, the pixel-to-bin map, the corrections, the ROI map - with a blocking NULL-stream cudaMemcpy, and then reads them from kernels on its own stream. A pageable host-to-device cudaMemcpy returns once the source has been staged, with the DMA still in flight, and a non-blocking stream no longer waits for the NULL stream. The failure mode is a silently unapplied mask or a stale mapping, not a crash, so it would not have announced itself. Put them on the stream the engine already owns, and synchronise once at the end of the constructor - that is required for the preprocessor, whose source is a local vector, and leaves the others settled rather than in flight for the cost of one one-time sync. The GPU spot-finder test uploaded its image the same way. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>	2026-07-31 11:51:22 +02:00
leonarski_fandClaude Opus 5	3e56d96921	Stills partiality: adopt the refined tilt only when it fits better ... RefineOne re-measured the image's correlation to the reference after writing the refined partialities - because --min-image-cc drops images by it - and then ignored what it measured. A crystal the tilt model suits worse than the fixed partiality it replaces kept the refined model anyway, and the refinement is on by default. Compare against the CC the crystal arrived with and put it back untouched when the refinement does not improve it, which is the same state a crystal with too few reflections to fit ends in. Also four things noted in review and left until now: AdaptiveThresholdTest.cpp was listed twice in the test target, AdaptiveThreshold.h was the one header in image_analysis/spot_finding not in its library's source list, CLAUDE.md said update_version.sh rewrites VERSION when it only reads it, and the CHANGELOG did not mention that image_scale_b is gone from the plot_type enum - which breaks a client that asks for that plot. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>	2026-07-30 22:03:18 +02:00
leonarski_fandClaude Opus 5	04450eb618	Adaptive spot finder: sum the rings across blocks in double ... The ring sigma is the cancelling difference sum2/n - m^2, and both sums were float accumulated by atomics whose order is arbitrary. Two costs: the cancellation left only ~4 digits in the variance, and the ordering moved the resulting threshold by ~0.05 counts between runs - enough to flip a pixel sitting on the hard "value >= threshold" test, and with it a connected component's size. So the GPU engine did not reproduce the CPU one and did not reproduce itself. Only the accumulators that span blocks are widened. The per-block staging stays float, because a block contributes a few dozen similar-magnitude pixels to a ring and there is nothing to lose there - that also keeps the shared-memory footprint of the hot loop, and hence its occupancy, exactly as it was: measured on a 4.5 MP frame, 0.960 vs 0.966 ms/frame (40.9x over the CPU path, unchanged). finalize_rings now does the cancellation in double and rounds to float last, which is what AdaptiveSpotFinderCPU::AccumulateRings does. The device properties are also read from the current device rather than device 0; callers round-robin engines across GPUs. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>	2026-07-30 11:05:54 +02:00
leonarski_fandClaude Opus 5	009555bc49	Spot finding: a zero high-resolution limit means no limit here too ... Every other reader of spot_finding.high_resolution_limit spells "unset" as value_or(0) and compares, so 0 and nullopt are interchangeable - except in SpotAnalyze, which passed the 0 straight to ResolutionShells and threw "Resolution must be above zero" on every image. Reachable over the REST API, where 0 is the natural way to say "no limit" and the settings check lets it through; the rugnux CLI already maps 0 to unset before this point. While here, check that a limit that IS set is finite regardless of its sign - NaN fails the > 0 test and was skipping validation entirely. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>	2026-07-30 10:55:19 +02:00
leonarski_fandClaude Opus 5	16bf3408f0	Address code-review findings; make detection limits detector-driven ... One changeset, developed together in response to a review of this branch, so the files carry several of the changes at once. Full test suite passes (733 cases). Spot finding - Split ImageSpotFinder into Detect() (flag strong pixels - the expensive per-pixel pass) and ExtractSpots() (CCL + min/max-pix + resolution mask), with Run() = both. The per-image min-pix escalation now detects ONCE and repeats only the cheap extraction, instead of re-running the whole finder four times per frame as it did on the default path. It also keeps the winning attempt's spot list rather than re-extracting it, so the frame that is integrated is exactly the frame that was scored - which a GPU re-extract could not guarantee (float atomic ordering). - spot_finding_time_s no longer swallows indexing time, and indexing_time_s now sums every escalation call instead of reporting only the last. Detection limits follow the detector - The azimuthal-integration upper q and the spot-finding high-resolution limit are now std::optional, in the C++ structs AND in the OpenAPI schema, and resolve to the detector's own maximum (DiffractionExperiment::GetDetectorMaxQ_ recipA). Adaptive detection reads a pixel's ring from the azimuthal bins, so a pixel outside that q range could never be strong - the integration range silently bounded what detection could see, regardless of the requested resolution limit. Regenerated the C++ and TypeScript clients; the viewer and the web frontend each gained a "to detector edge" switch. Detection defaults are now per workflow (measured, not assumed) - Stills: adaptive detection, min-pix chosen per image, no resolution clipping. - Rotation: fixed-threshold finder, min-pix 2, 1.5 A limit. On a 33-crystal rotation battery, adaptive detection helped four hard crystals but deterministically broke three (a lost space group, a halved indexing rate, a collapsed merge), and the detector-edge limit cost indexing on a strong rotation set (100.0 -> 96.8%). Each is still overridable by its flag, and --no-adaptive-spots is new. Indexer seed escalation - Stop escalating once a seed's lattice explains >= 90% of the seed spots. Previously any frame with >= 80 spots always paid three indexer calls, online broker included. Merge-consistency filter - --min-image-cc gated on a per-image CC computed BEFORE the stills partiality post-refinement and never refreshed; the refiner now recomputes it, so the reported CC describes the data that are actually merged. - Replaced the per-call cc_mask argument with one MergeOnTheFly flag, so the merge, the error model and MergeStats can no longer disagree about which images are in (the --scale path merged unfiltered while its statistics were filtered). Per-image B-factor refinement (-B) removed - Measured on four serial-stills datasets: it is a no-op where the per-image fit is well conditioned and actively harmful where it is not (CC1/2 -8.1, R_meas +23.2 on the weakest large-cell set, whose fits hit their [-50, 200] bounds on 14-25% of images). It had also been silently DISCARDED since the partiality post-refinement landed - reported but not applied. Rather than fix and keep a knob with no demonstrated benefit, the flag and the whole image_scale_b_factor chain are gone: setting, scaling fit, message field, CBOR, HDF5 write and read-back, per-image plot, OpenAPI enum, viewer column and checkbox, docs. ScaleOnTheFly no longer needs Ceres at all - the fit is a linear IRLS. (The Wilson per-image b_factor is a different quantity and stays.) Stills partiality width now fits both of its components - sigma^2 = gamma0^2 + (gamma_e*d*)^2 instead of a purely angular gamma_e*d* with gamma0 pinned to 0. Fitted per crystal by least squares of dist_ewald^2 on d*^2. The angular-only width is fitted over a d*^2-dense population, so it was pinned by the high-resolution edge and collapsed at low d*: median partiality 0.008 beyond 13 A for reflections that were plainly recorded, 55% of them under the merge's partiality floor, and the survivors divided by those values - which inflated the merged low-resolution intensity scale 3.6x (~ +9 A^2 of apparent B). Measured on 5000 stills: the ramp flattens to 0.89x, no observation is dropped any more (701750 -> 716811), shell-mean CC1/2 and R-free improve slightly. Note CC1/2, R_meas, completeness and a B-refining R-free are all blind to that ramp, which is why it survived earlier validation; the cost is high-resolution R_meas (98.5 -> 101.9 shell-averaged). Removed dead code from add-then-remove churn - Prediction-time "still partiality" (unreachable: no setter), the phantom IndexingSettings::min_indexed_spot_fraction knob (getter, no setter - now the constant it always was), StillsPartialityRefine's caller-less Settings constructor and its reference to a long-gone env var, ProcessImage's unread bool return, an unused include, and a dead viewer overlay hook. Also - Viewer: the magnifier compared a QImage with itself, so its scene rect was set once ever and it could not pan into a larger dataset; the hover tail timer could fire after leaveEvent and resurrect the resolution readout outside the image. - update_version.sh regenerated the frontend lock file BEFORE bumping the version (every release shipped an off-by-one lock), and did git rm/git add on a path that has not existed since the client moved to src/client - with no set -e, both failed silently. - fpga/pcie_driver/postinstall.sh tested "[ ! occurrences > 0 ]", which is a redirect, not a test, so dkms add never ran. - Unit tests for the adaptive-threshold host functions, which had none. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>	2026-07-27 09:07:00 +02:00
leonarski_fandClaude Opus 4.8	a8c1006c49	Choose min-pix-per-spot adaptively per image for serial-stills indexing ... For stills indexing the minimum-pixels-per-spot filter is now chosen per image instead of being fixed: the frame is indexed at min-pix 3/2/1 and the setting that maximises indexed-spot count weighted by indexed fraction (n_indexed^2 / n_total) is kept, then integrated once at that min-pix. The fraction factor keeps a smaller min-pix's extra spots only when the lattice actually explains them, so strong frames retain their real weak spots (extending resolution) while noise-flooded frames stay strict. The mode is selected by the presence of --min-pix-per-spot, now optional (SpotFindingSettings::min_pix_per_spot is std::optional<int64_t>): omit it for the adaptive per-image path, give a value to force a fixed min-pix. It applies only to the stills indexing path -- rotation indexing builds one global lattice and keeps a fixed min-pix, and the online receiver and the FPGA host path always carry a concrete value, so neither changes. IndexAndRefine::ProcessImage now returns whether the frame indexed, to drive the per-image selection. Exposed in the jfjoch_viewer spot-finding settings (adaptive-threshold and adaptive-min-pix checkboxes, each greying out the control it overrides); the broker uses neither. Validated on the full rotation regression battery (no regression) and the whole serial-stills target battery at full image count. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>	2026-07-26 18:31:35 +02:00
leonarski_fandClaude Opus 4.8	9fdeed282a	Add fused GPU adaptive spot finder (azint + spot finding in one pass) ... AdaptiveSpotFinderGPU does the per-resolution-ring reduction once on the GPU and drives both products from it: the azimuthal-integration profile (corrected space) and the self-calibrating adaptive spot-detection threshold (raw counts). This replaces the separate GPU azint pass and the host-side adaptive spot finder that runs on the GPU path today. On a ~4.5 MP detector it does both jobs in ~1 ms/frame versus ~40 ms for the CPU adaptive finder (~42x), with an identical spot list and azimuthal profile. The per-ring threshold math (Poisson tail + read-floored Gaussian, operating point from the false-pixels-per-frame knob) is factored into AdaptiveThreshold.h so the CPU and GPU finders share one source of truth and cannot drift. Wired opt-in via a MXAnalysisWithoutFPGA constructor flag, default on for the rugnux offline path and the interactive viewer, off for the online receiver (so the broker path is unchanged). When on, Analyze() skips the separate azint pass and lifts the profile from the fused engine. The viewer gains an "Adaptive threshold" checkbox that greys out the signal/noise and photon-count sliders (the adaptive finder uses neither). Dedicated tests exercise both products (spot-finding parity vs the CPU finder, azimuthal profile vs a standalone GPU azint) plus a speed benchmark. Validated end-to-end on lysozyme serial stills: fused == CPU-adaptive index rate and merge stats. Docs: new section 3.2 in docs/CPU_DATA_ANALYSIS.md. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>	2026-07-25 20:10:45 +02:00
leonarski_fandClaude Opus 4.8	20bbcb1cd3	Remove --soft-weight and --local-snr spot-finder options ... Both were opt-in adaptive-spot refinements that did not help. Soft per-spot weighting was index-rate neutral across the battery (re-ranking only bites when spots exceed the max-spot cap, which weak serial data does not reach). The local-SNR gate was neutral on index rate and degraded merged CC1/2 on flooded XFEL data. Drops the flags, ApplyWeights/FilterByLocalSNR, the per-spot weight field, and the by-weight FilterSpotsByCount branch (now strongest-first only). --adaptive-spots itself is unchanged. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>	2026-07-25 17:31:35 +02:00
leonarski_fandClaude Opus 4.8	ecf79af018	Remove threshold-free persistence spot-detection variant ... Drops --persistence-spots and AdaptiveSpotFinderCPU::RunPersistence (the 0-D topological-persistence detector added in 5a33b0743). It was a research variant that never beat the hard-threshold adaptive detector on a CC1/2 basis and is a GPU dead-end (global candidate sort + union-find), so it is not a production path. The hard-threshold --adaptive-spots detector is unaffected. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>	2026-07-25 12:41:44 +02:00
leonarski_fandClaude Opus 4.8	ca7cbe206a	Add opt-in local-SNR spot gate and acceptance-fraction knob (serial stills) ... Two opt-in tools for weak serial-stills tuning; both default-off, so the default pipeline is bit-identical (verified: a serial-stills reference run reproduces HEAD's 7.85% indexing rate exactly). --local-snr <sigma> (AdaptiveSpotFinderCPU::FilterByLocalSNR): after the loose per-ring adaptive threshold builds connected-component spots, drop any spot that does not stand this many sigmas above its OWN LOCAL background (robust median/MAD of a square annulus), not just the azimuthal ring mean. On structured-background (XFEL) frames the ring mean underestimates the local diffuse level in some sectors, so the ring threshold floods; a real Bragg peak still stands many local sigmas proud. Validated on XFEL stills to separate real peaks from flood at the pixel level (real median local-SNR ~70 vs flood ~2.6; SNR>=5 keeps ~99.8% of real peaks, ~14% of flood). GPU-portable (a per-spot local reduction). NOTE: on the current serial-stills battery it is index-rate/CC1/2 neutral -- the flood that survives as CC clusters overlaps weak-real spots, and only lattice-fit separates those -- but it is the correct tool for genuinely floody data (ice/jet/loosened detector) and the right substrate for the online FPGA path. --min-indexed-fraction <f>: exposes the previously hardcoded 0.20 minimum indexed-spot fraction (AnalyzeIndexing) as a per-run setting. Lowering it admits weaker/sparser crystals; on flooded XFEL data the extra lattices are spurious (pair with --min-image-cc to gate them), on clean synchrotron data there are no marginal frames so it is a no-op -- useful as a gating-experiment primitive. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>	2026-07-24 11:12:22 +02:00
leonarski_fandClaude Opus 4.8	7c5bedfd74	Add soft per-spot quality weighting for adaptive spot detection ... Add --soft-weight (implies --adaptive-spots): give every detected spot a continuous quality weight in (0,1] and keep the highest-weight spots rather than the brightest, so a deliberately loose detector self-cleans -- bright ice / salt / jet blobs and single-pixel noise no longer evict faint clean Bragg spots from the max-spots cut. The weight is a product of dimensionless gates (AdaptiveSpotFinderCPU::ApplyWeights, computed against the per-ring background the adaptive finder already builds): a logistic ramp in the spot's SNR and a soft size band (rises from one pixel, plateaus, falls for oversized ice/salt/streak blobs). It carries on DiffractionSpot -> SpotToSave and is consumed by FilterSpotsByCount, which ranks by {non-ice, weight, intensity} when requested and by intensity otherwise, so the classic and FPGA paths are unchanged. Honest result: on the serial-stills battery this is index-rate-NEUTRAL. The weighted ranking only changes the outcome when the spot count exceeds the max-spots cap and the weight disagrees with intensity in a way that affects indexing; the adaptive detectors already produce clean spot lists and the weak sets sit under the cap, so re-ranking is a wash there (and a wash, not a regression, on the one set that floods). Its intended benefit -- robustness to ice/jet-contaminated frames and to a loosened detector -- is not exercised by this battery; kept opt-in as the substrate for that. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>	2026-07-23 19:53:55 +02:00
leonarski_fandClaude Opus 4.8	6de03bc443	Add threshold-free persistence variant of adaptive spot detection ... Add --persistence-spots, a second parameter-free detector alongside --adaptive-spots. Instead of a hard per-ring threshold it builds the noise-normalised image z = (I - ring_mean) / sqrt(ring_sigma^2 + read^2) (same per-ring background as the hard variant) and scores every intensity maximum by its 0-D topological persistence: sweeping the height from high to low, each maximum is born and, when its basin meets a taller one at a saddle, dies with persistence = birth - saddle, in sigma. A lone noise spike merges into the background almost immediately (persistence ~1 sigma); a real peak stands many sigma proud. Emitting maxima whose persistence clears the same z(E) significance bar needs no photon threshold and no min-pix, and it deblends touching peaks (each keeps its own maximum). Implemented with the same union-find idiom as the connected-component labeller. On serial stills this auto-adapts with no per-dataset tuning like --adaptive-spots, finding fewer but cleaner (deblended) spots; the hard-threshold variant remains more sensitive on the very weakest data. Both share the per-ring background and read-noise floor. comp_of is allocated lazily so the default and hard-adaptive paths pay nothing. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>	2026-07-23 17:38:18 +02:00
leonarski_fandClaude Opus 4.8	9a8c946555	Add self-calibrating adaptive spot detection for offline stills ... The offline CPU spot finder marks a pixel strong when it clears a fixed photon count AND a local-window SNR. The fixed photon floor forces per-dataset tuning: its sweet spot tracks the background level (weak sets want a low threshold, strong or high-background sets a high one) and the usable window is narrow, so users hand-tune --spot-threshold/--spot-sigma per dataset. Add an opt-in --adaptive-spots mode (AdaptiveSpotFinderCPU) that replaces the fixed floor with a per-resolution-ring threshold derived from each image's own noise. Per ring it computes a peak-excluded background mean and sigma (one plain pass + two sigma-clip passes over the assembled photon image, binned by the azimuthal-integration ring index) and sets thr = max( PoissonTail(mean, p), mean + z * sqrt(sigma^2 + read^2) ) with p = false_pixels_per_frame / n_pixels the single portable knob (default 100) and z = Phi^-1(1 - p). The Poisson arm is the correct significance where the background is countable (it carries the sqrt(mean) shot noise, so a bright low-resolution ring gets a high threshold); the read-noise-floored Gaussian arm keeps the threshold physical where the background vanishes (empty high-resolution rings), without which those rings flood. read is a detector-level constant, not a per-dataset knob. Both arms are needed: Poisson alone floods near-zero background, Gaussian alone drops the shot-noise term and under-thresholds bright rings. One --adaptive-spots setting then adapts across a wide range of serial datasets with no per-dataset threshold, matching or beating hand-tuned thresholds and the peakfinder8/xgandalf reference on both weak large-cell and strong serial data, with equal merged R-free. The finder runs on the CPU (offline/viewer path) and reads the host image, which the GPU pipeline already keeps in sync, so it works in either build. The default (non-adaptive) path and the online/FPGA path are unchanged. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>	2026-07-23 17:23:19 +02:00
leonarski_fandClaude Opus 4.8	81dbf9a385	Fix empty spot-plot and resolution percentile in SpotAnalyze ... GenerateSpotPlot iterated msg.spots, but SpotAnalyze called it before assigning output.spots. In the online path the DataMessage is fresh per frame, so the plot was built from an empty list and spot_plot_intensity / spot_plot_count came out all zeros. Pass the finished spots vector explicitly instead of relying on the field being set: the live path passes the full pre-truncation list, the HDF5 read-back path passes message.spots. GetResolution scaled the 5th-percentile index by spots.size() (which includes ice-ring spots) while indexing the ice-filtered resolutions vector, biasing the estimate and reading out of bounds on ice-heavy frames. Index by resolutions.size() instead. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>	2026-07-21 09:53:33 +02:00
leonarski_f	d6389e12da	v1.0.0-rc.156 (#66) ... This is an UNSTABLE release. It includes many experimental features, as well as many AI generated fixes. We recommend using rc.152 for production use. * jfjoch_process: Major rotation (rot3d) data processing overhaul - robust profile-fit integration, Cauchy-loss scaling with optional absorption surface, de-novo indexing and space-group/centering determination fixes, and merging statistics + ISa in the mmCIF output. * jfjoch_process: Add EXPERIMENTAL ice-ring detection (--detect-ice-rings) that excludes ice reflections from scaling. * Compression: Add BSHUF_ZSTD_RLE_HUFF, make compression size-aware (drop frames that don't fit rather than aborting), and add the jfjoch_recompress tool. * jfjoch_viewer: Report "Multiple lattices detected" and grey out "Analyze dataset" on a live connection. * jfjoch_broker: Write smargon chi/phi goniometer positions to NXmx; read sensor thickness/material from HDF5 metadata. * CI: Build Windows (CUDA and non-CUDA) installers.Reviewed-on: #66 Co-authored-by: Filip Leonarski <filip.leonarski@psi.ch>	2026-07-03 19:18:56 +02:00
leonarski_f	75e401f0e5	v1.0.0-rc.153 (#63) ... This is an UNSTABLE release. It includes many experimental features, as well as many AI generated fixes. We recommend using rc.152 for production use. * jfjoch_broker: Add EXPERIMENTAL pixelrefine mode for image processing * jfjoch_broker: Allow to load user mask from 8-bit and 16-bit TIFF files * jfjoch_broker: Add ROI calculation in non-FPGA workflow * jfjoch_broker: Fixes to TCP image pusher * jfjoch_broker: Remove NUMA bindings * jfjoch_broker: Improvements to indexing * jfjoch_broker: For PSI EIGER, trimming energies are taken from the detector configuration (now compulsory) instead of hardcoded values * jfjoch_writer: Save ROI definitions and the per-pixel ROI bitmap in the master file; azimuthal ROIs support phi (angular) sectors * jfjoch_viewer: Major redesign with dockable panels and saved layouts, plus on-canvas creation/move/resize of box, circle and azimuthal ROIs * jfjoch_viewer: Run jfjoch_process reprocessing jobs from inside the GUI and overlay per-run results Reviewed-on: #63	2026-06-23 20:29:49 +02:00
leonarski_f	cc3eb8352c	v1.0.0-rc.148 (#58) ... This is an UNSTABLE release. The release has significant modifications for data processing - in case of troubles go back to 1.0.0-rc.144. * jfjoch_broker: Improve azimuthal integration (add <I^2> calculation) * jfjoch_broker: Fixes around indexing, aiming to handle multi-lattice crystals (work in progress, it is not fully integrated) * jfjoch_writer: Save mean(I), stddev(I), and count(I) for each azimuthal bin Reviewed-on: #58	2026-06-08 08:30:35 +02:00
leonarski_f	d760b12a18	v1.0.0-rc.141 (#51) ... This is an UNSTABLE release. The release has significant modifications and bug fixes, if things go wrong, it is better to revert to 1.0.0-rc.132. * jfjoch_broker: Azimuthal integration mapping is generated with parallel computations, significantly reducing setup times * frontend: Fix selection of FFTW in indexing settings Reviewed-on: #51 Co-authored-by: Filip Leonarski <filip.leonarski@psi.ch> Co-committed-by: Filip Leonarski <filip.leonarski@psi.ch>	2026-04-30 13:04:54 +02:00
leonarski_fandtakaba_k	230480e390	v1.0.0-rc.138 (#48) ... This is an UNSTABLE release. The release has significant modifications and bug fixes, if things go wrong, it is better to revert to 1.0.0-rc.132. jfjoch_broker: Cleanup DECTRIS start-up code to enable a shorter start time jfjoch_broker: Allow for asynchronous start to allow overlapping detector configuration with other beamline preparations jfjoch_broker: Goniometer axis name is converted to lowercase jfjoch_broker: Fix bug, where wrong HTTP error codes were returned jfjoch_broker: Improve sigma estimation during merging (K. Takaba) --------- Co-authored-by: takaba_k <kiyofumi.takaba@psi.ch> Reviewed-on: #48 Co-authored-by: Filip Leonarski <filip.leonarski@psi.ch> Co-committed-by: Filip Leonarski <filip.leonarski@psi.ch>	2026-04-27 19:56:14 +02:00
leonarski_f	c981e1b91c	v1.0.0-rc.137 (#46) ... This is an UNSTABLE release. The release has significant modifications and bug fixes, if things go wrong, it is better to revert to 1.0.0-rc.132. * jfjoch_broker: Better track time for each operation in the processing stack * jfjoch_broker: Rewrite preprocessing of diffraction images in the non-FPGA workflow to better use GPUs (work in progress) * jfjoch_broker: Remove ROI calculation in the non-FPGA workflow (work in progress) * jfjoch_viewer: Toolbar displays image number starting from 1 (instead of 0) Reviewed-on: #46	2026-04-25 19:59:21 +02:00
leonarski_f	bb9f5c715f	v1.0.0-rc.135 (#44) ... This is an UNSTABLE release. The release has significant modifications and bug fixes, if things go wrong, it is better to revert to 1.0.0-rc.132. * Multiple small bug fixes scattered across the whole code base. (detected with GPT-5.4) * jfjoch_viewer: Improve image render performance Reviewed-on: #44 Co-authored-by: Filip Leonarski <filip.leonarski@psi.ch> Co-committed-by: Filip Leonarski <filip.leonarski@psi.ch>	2026-04-16 11:59:59 +02:00
leonarski_f	06949caf1a	v1.0.0-rc.112 (#18) ... This is an UNSTABLE release and not recommended for production use (please use rc.11 instead). * jfjoch_broker: Experimental rotation (3D) indexing * jfjoch_broker: Minor fix to error in optimizer potentially returning NaN values Reviewed-on: #18 Co-authored-by: Filip Leonarski <filip.leonarski@psi.ch> Co-committed-by: Filip Leonarski <filip.leonarski@psi.ch>	2025-11-30 17:39:22 +01:00
leonarski_f	061152279c	v1.0.0-rc.91	2025-10-20 20:43:44 +02:00
leonarski_f	14f5051692	1.0.0-rc.89	2025-10-01 22:54:40 +02:00
leonarski_f	a48d8fb5b9	1.0.0.rc-88	2025-10-01 11:18:10 +02:00
leonarski_f	99b7dc07f7	1.0.0-rc.87	2025-09-30 20:43:53 +02:00
leonarski_f	5d9d2de4a4	v1.0.0-rc.81	2025-09-21 19:27:51 +02:00
leonarski_f	dba807fadd	v1.0.0-rc.71	2025-08-28 07:07:01 +02:00
leonarski_f	bb32f27635	v1.0.0-rc.70	2025-08-27 06:21:10 +02:00