9fdeed282a7d83eadb5c566a1b9a6dc86185c7f3
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>
Jungfraujoch
Application to receive data from the PSI JUNGFRAU and EIGER detectors.
All documentation is now placed in docs/ subdirectory and for the current version hosted on Jungfraujoch Read The Docs page.
Languages
C++
73.7%
HTML
8.8%
C
7%
TypeScript
4.8%
Tcl
2.5%
Other
3.1%