- Capitalize Rugnux as a proper noun throughout the prose; the command stays lowercase `rugnux` in code font. RUGNUX_OVERVIEW.md is retitled "What Rugnux does". - ACKNOWLEDGEMENT.md cites the raw-data repositories only: dataset counts and DOI prefixes moved out (EXTERNAL_TEST_DATA.md owns them), the ESRF data portal gains its citation (Dimper et al. 2019), and MXRDR remains name + link - it has no canonical citation paper. - RUGNUX_FORMATS.md: the CCD formats (marCCD, SMV) are supported as-is with very limited scope, and per-panel XFEL data is not read. - Fix wrong facts a reader would act on: nonexistent `make jfjoch` targets, invalid udev rules, PUSH sockets documented as PULL, swapped writer width/height, underload semantics, the transposed pixel-mask numpy example (the server checks width and height separately), the Durin/Neggia mask-bit table, FPGA threshold register addresses and the mailbox bit field, the I2C core's document number (PG090), an inverted MODEL_FIT_SIGMA formula, a self-inconsistent worked report example, and 11 cross-page anchors whose slugs carry MyST section numbers. - Unify CC1/2 spelling in prose; math notation and report keys unchanged. - Sweep grammar, typos and editing residue across the FPGA, deployment, streaming and analysis pages, including historical CHANGELOG typos. - rugnux_cli.cpp: the -S usage/error examples pair 96 with P43212; 92 names a different group. - Root THIRD_PARTY_NOTICES.md: scope the GPL-compatibility claim (CUDA EULA) and the vendored-table intro (traccc); the docs copy regenerates via update_version.sh. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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FPGA data flow
The following steps are performed on FPGA (in the order of operation):
- UDP header decoding
- SLS detector header decoding
- State machine that controls data acquisition (start/stop/cancel)
- High-bandwidth memory cache to buffer network packets and reorder them to form full modules
- ADU histogram for JUNGFRAU
- Mask pixels from missing packets with special value
- Reorder lines for EIGER to form a proper module
- Mask pixels based on provided pixel mask
- JUNGFRAU conversion with gain and pedestal corrections
- Threshold: pixel values below a set minimum are zeroed, values above a set maximum saturated
- Frame summation (up to 256 frames)
- Integration according to predefined map (e.g., 1D azimuthal integration)
- Spot finding
- ROI calculation
- Image lossy compression using N*sqrt(pixel) values
- Send images, analysis results and metadata to host memory via PCI Express
Each step has a dedicated core, written in high-level synthesis. Exact operation of cores for data analysis is explained in dedicated document.