leonarski_f
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* rugnux now tells you whether a crystal diffracts anisotropically and how far it reaches in each direction, without a second program: a new `9. DIFFRACTION ANISOTROPY` section in `<prefix>_report.txt` and matching `_reflns.pdbx_aniso_B_tensor_*` / `_reflns.jfjoch_aniso_*` items in the merged mmCIF report the anisotropic deltaB, the diffraction limit along each principal direction, and a `NOT DETECTED` / `DETECTED` / `CANNOT DETERMINE` verdict measured against the data set's own systematic error. It is a description only - no intensity is corrected, no reflection is removed, and the merged data do not depend on direction.
* rugnux can hand its integrated observations to another scaling program: `--export-unmerged` writes `<prefix>_unmerged.mtz`, an unmerged MTZ readable by aimless, pointless, careless and `iotbx.merging_statistics`, in `--mode mx` and `--mode scale` alike. Each rotation reflection's partials are summed into one full; `--export-unmerged-partials` writes one row per image instead. Intensities carry the Lorentz-polarization factor and nothing else, since those programs scale the data themselves. Lattice-centring absences are not written; screw and glide absences are.
* rugnux integrates crystals with broad spots better - where it changes anything, per-shell mean I/sigma improves by up to 31% and R_meas by up to 24% - because on rotation data the integration signal radius is now taken from the crystal's own measured spot width instead of a fixed 4 px. `--adaptive-integration-radius=off` restores the fixed radius and an explicit `--integration-radius` still overrides both. The widened radius applies to the final integration pass only, and a pattern too dense for it is re-integrated at 4 px with a note in the log.
* rugnux discards fewer stills reflections for want of a background ring, improving per-shell R_meas over most of the signal-bearing range: the stills background ring now runs to 14 px instead of 12. The gain reverses in shells below a mean I/sigma of about 4.
* rugnux determines the space group with thresholds that mean the same thing on a weak crystal as on a strong one: symmetry operators are scored on resolution-normalised intensities (E squared) instead of raw merged intensities, and a reflection counts as genuinely present on its counting significance instead of on the merged I/sigma, which saturates at the merge's own ISa. The search resolution cut is no longer able to move the answer, and the twin-law H bound moves from 1.70 to 1.85, which stops one class of correct high-symmetry assignment being refused as twinning.
* rugnux says what the space-group search tested and what it could not: the twin-law disagreement H is printed for every operator together with the adopted point group's H ratio and its bound; alternatives that are not on the reported lattice are named with how their cell differs; and a lattice centring the data could not test - the crystal having been integrated on the primitive sub-cell, so the reflections it extinguishes were never measured - is marked `UNTESTED` and warned about where it is adopted, as coming from the lattice metric rather than from the intensities.
* rugnux `--mode scale` re-merges a `_process.h5` in the right symmetry without being told it: the file now records the space group on every run - a two-pass rotation run wrote none before, so re-merging defaulted to P1 - together with the change of basis under `/entry/MX/reindexMatrix` where the lattice was re-seated, and `--mode scale` also reports the Wilson B-factor estimate instead of `WILSON_B= nan`. A file written before this stops with a message naming the two cells and the override to use, instead of failing inside the merge. A third-party reader of a `_process.h5` must apply `reindexMatrix` where it is present.
* rugnux installs on its own, as a package called `rugnux` - `dnf install rugnux` or `apt install rugnux` - instead of arriving inside `jfjoch-viewer`. It pulls in none of the acquisition stack, so a machine that only processes data no longer has to carry the broker, the detector libraries or Qt to get it. Installing it over a `jfjoch-viewer` from rc.163 or earlier, which still owns `/usr/bin/rugnux`, upgrades cleanly rather than failing on the duplicate file.
* rugnux is also a standalone download, built for arm64 as well as x86_64: `rugnux-<version>-linux-{x86_64|aarch64}-cuda<major>.tgz` and `rugnux-<version>-win64-cuda<major>.zip` on the release page, for machines that are not managed by a package manager. The aarch64 build targets GH200 and DGX Spark, and is untested on hardware.
* Every portable Linux binary is now a single self-contained file: cuFFT is linked statically instead of being shipped beside the executable and found through an rpath, so `rugnux` and `jfjoch_viewer` need nothing but an NVIDIA driver, and only to use the GPU. The `.rpm`/`.deb` continue to take cuFFT from the distribution. The developer utilities `jfjoch_extract_hkl` and `jfjoch_recompress` are no longer packaged anywhere.
* Jungfraujoch needs six fewer shared libraries on the machine - libopenblas and libmetis, and libgfortran, libquadmath, libgomp and libz behind them - because the Ceres LAPACK, METIS and SuiteSparse back-ends are no longer built. Nothing in the code ever selected them, and results are unchanged.
* The PCIe driver DKMS package builds for the kernel it is being installed for instead of the running one, so a module built while a kernel update is being applied loads after the reboot.
* The PCIe driver builds on RHEL 9.5 and later, and on their CentOS Stream, Rocky and AlmaLinux equivalents, where the `vm_flags` kernel interface was backported into the 5.14 kernel.
* A data collection started with `async_start` that fails to start - a writer refusing to overwrite an existing file, for instance - is reported as an error by `/wait_until_running` and `/wait_till_done` instead of as a timeout and a successful collection respectively. The error message is the one the writer gave.
* A calibration that is cancelled or that fails to collect its pedestals is no longer reported as a successful one. The broker goes to `Inactive` with an error message and has to be initialized again, instead of sitting in `Idle` looking ready to measure while holding partial pedestals - data collected in that state was silently mis-converted.
* A failed `/initialize` is reported to `/wait_until_running` and `/wait_till_done` as soon as it happens, instead of when their timeout expires.
* `space_group_number` accepts space groups up to 230 in the API schema, so cubic space groups can be recorded. The broker always accepted them; the generated clients rejected them before the request was sent.
* The results report's `REPORT_VERSION` is 3, two sections having been added. Existing key names and table columns are unchanged.
* The merged statistics table has **9** resolution shells instead of 10, which is what XDS reports. The bins were already XDS's - equal steps in 1/d^2 between the lowest- and the highest-resolution reflection the merge kept - so at the same resolution limits the two tables now have the same shell boundaries and can be read row for row. `--resolution-shells` sets a different count.
* `rugnux --model` now settles the frame the merged reflections are written in, not only the frame the R-factors and the maps are computed in: the `.mtz`/`.cif`/`.hkl` come out in the model's indexing, and where the data were merged in the model's enantiomorph they take the model's hand and space group - which on anomalous data puts I(+) and I(-) the right way round. The indexing choice is logged with the winning R-free and the runner-up, so a decision made within noise is visible.
* `rugnux --model` can resolve the indexing ambiguity of a **serial stills** run, which a model could not do before: structure factors computed from the model become the per-image reference, the same role a reference MTZ plays. It needs the cell and space group up front (`-C` / `-S`). Without one or the other, a merohedral serial run still merges both hands together and says so.
* The rugnux documentation opens with a quick start - the default run, and runs with a reference MTZ, with a model, or with the space group and cell pinned - and explains the indexing ambiguity: what it costs on rotation and on serial data, and which of `-z` / `--model` resolves it in each case. The long reference pages now carry a table of contents.
Reviewed-on: #74
Co-authored-by: Filip Leonarski <filip.leonarski@psi.ch>
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# Acknowledgements
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Citation: F. Leonarski, M. Bruckner, C. Lopez-Cuenca, A. Mozzanica, H.-C. Stadler, Z. Matej, A. Castellane, B. Mesnet, J. Wojdyla, B. Schmitt and M. Wang "Jungfraujoch: hardware-accelerated data-acquisition system for kilohertz pixel-array X-ray detectors" (2023), J. Synchrotron Rad., 30, 227-234 [doi:10.1107/S1600577522010268](https://doi.org/10.1107/S1600577522010268).
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The project is supported by :
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* Innosuisse via Innovation Project "NextGenDCU high data rate acquisition system for X-ray detectors in structural biology applications" (101.535.1 IP-ENG; Apr 2023 - Sep 2025).
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* ETH Domain via Open Research Data Contribute project (Jan - Dec 2023)
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* AMD University Program with donation of licenses of Ethernet IP cores and Vivado software
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Decoding bitshuffle+LZ4 images on the GPU, rather than decompressing them on the host and uploading
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the result, follows Jon Wright (ESRF): "Experiences with GPU decompression for bitshuffle + LZ4
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data", HDF5 User Group meeting (2021), and [bslz4decoders](https://github.com/jonwright/bslz4decoders).
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The CUDA kernels in Jungfraujoch are its own, but the approach is his.
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Spot extraction groups strong pixels into spots with the sparse connected-component labelling of the
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ACTS traccc project: P. Gessinger, H. M. Gray, A. Krasznahorkay, C. Leggett, J. Niermann,
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A. Salzburger, S. N. Swatman and B. Yeo, "traccc: GPU track reconstruction library for HEP
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experiments" (2025), [arXiv:2505.22822](https://arxiv.org/abs/2505.22822);
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[traccc](https://github.com/acts-project/traccc). The CPU spot extractor adapts its SparseCCL source,
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and the CUDA spot extractor follows the design of its GPU counterpart - a backward-neighbour graph
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over a sorted hit list, resolved by a parallel union-find. traccc is MPL-2.0; see
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[THIRD_PARTY_NOTICES.md](THIRD_PARTY_NOTICES.md).
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This software uses Viridis, Magma and Inferno colormaps from Matplotlib under its BSD-compatible license
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## Crystallographic methods adopted from other packages
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The analysis pipeline reimplements methods first published, and in most cases first implemented, by
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other crystallographic software. The code below is Jungfraujoch's own; the methods are theirs, and
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are acknowledged here. Where a package's source was consulted this is said explicitly. None of these
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packages is linked or vendored, with the single exception of GEMMI (see
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[THIRD_PARTY_NOTICES.md](THIRD_PARTY_NOTICES.md)).
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**[XDS](https://xds.mr.mpg.de/)** — rotation geometry and notation, the reciprocal Lorentz and
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partiality treatment, the maximum-likelihood mosaicity estimate, the `MINPK` criterion for rejecting
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a reflection whose predicted profile is not cleanly its own, the intensity-based test for a
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centred lattice, and the scaling correction surfaces indexed by image number and detector region. W. Kabsch, "XDS" (2010), Acta Cryst. D66, 125-132
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[doi:10.1107/S0907444909047337](https://doi.org/10.1107/S0907444909047337); W. Kabsch, "Integration,
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scaling, space-group assignment and post-refinement" (2010), Acta Cryst. D66, 133-144
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[doi:10.1107/S0907444909047374](https://doi.org/10.1107/S0907444909047374).
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**Profile fitting** with reweighted, de-biased variances is the Kabsch/Otwinowski iteration, from the
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second XDS paper above and from Z. Otwinowski and W. Minor, "Processing of X-ray diffraction data
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collected in oscillation mode" (1997), Methods Enzymol. 276, 307-326
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[doi:10.1016/S0076-6879(97)76066-X](https://doi.org/10.1016/S0076-6879%2897%2976066-X).
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**[DIALS](https://dials.github.io/)** — the resolution cutoff from the CC1/2 fall-off, per-observation
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outlier rejection at merge, the scaling error model, and the treatment of a reflection whose
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background is contaminated. Its published behaviour, and in places its source, settled several
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choices here. G. Winter, D. G. Waterman, J. M. Parkhurst et al., "DIALS: implementation and
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evaluation of a new integration package" (2018), Acta Cryst. D74, 85-97
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[doi:10.1107/S2059798317017235](https://doi.org/10.1107/S2059798317017235); D. G. Waterman,
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G. Winter, R. J. Gildea et al., "Diffraction-geometry refinement in the DIALS framework" (2016),
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Acta Cryst. D72, 558-575 [doi:10.1107/S2059798316002187](https://doi.org/10.1107/S2059798316002187);
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J. Beilsten-Edmands, G. Winter, R. Gildea et al., "Scaling diffraction data in the DIALS software
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package: algorithms and new approaches for multi-crystal scaling" (2020), Acta Cryst. D76, 385-399
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[doi:10.1107/S2059798320003198](https://doi.org/10.1107/S2059798320003198); J. M. Parkhurst,
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G. Winter, D. G. Waterman et al., "Robust background modelling in DIALS" (2016), J. Appl. Cryst. 49,
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1912-1921 [doi:10.1107/S1600576716013595](https://doi.org/10.1107/S1600576716013595).
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**[POINTLESS](https://www.ccp4.ac.uk/)** (CCP4) — the space-group search. Stage A scores each
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candidate rotation operator by the correlation of I(h) with I(Rh) on **resolution-normalised**
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intensities (E²), as POINTLESS does — both arms of a symmetry pair sit at the same |s|, so on raw
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intensities the resolution fall-off is variance shared between them and lifts a false operator's
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correlation as much as a true one's; the screw-axis test scores a
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predicted-absent class against the rest of its own axial row rather than against a global mean or a
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fixed cut, and lets confidence fall away with the number of axial reflections instead of refusing
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below a count. P. Evans, "Scaling and assessment of data quality" (2006), Acta Cryst. D62, 72-82
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[doi:10.1107/S0907444905036693](https://doi.org/10.1107/S0907444905036693); P. R. Evans, "An
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introduction to data reduction: space-group determination, scaling and intensity statistics" (2011),
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Acta Cryst. D67, 282-292 [doi:10.1107/S090744491003982X](https://doi.org/10.1107/S090744491003982X);
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P. R. Evans and G. N. Murshudov, "How good are my data and what is the resolution?" (2013), Acta
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Cryst. D69, 1204-1214 [doi:10.1107/S0907444913000061](https://doi.org/10.1107/S0907444913000061);
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J. Agirre, M. Atanasova, H. Bagdonas et al., "The CCP4 suite: integrative software for macromolecular
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crystallography" (2023), Acta Cryst. D79, 449-461
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[doi:10.1107/S2059798323003595](https://doi.org/10.1107/S2059798323003595).
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**[MOSFLM](https://www.mrc-lmb.cam.ac.uk/mosflm/)** — the Rossmann FFT autoindexing algorithm and
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post-refinement practice, including which parameters are safe to refine per image and which must be
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refined over a wedge. A. G. W. Leslie and H. R. Powell, "Processing diffraction data with MOSFLM"
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(2007), in *Evolving Methods for Macromolecular Crystallography*, NATO Science Series II, vol. 245,
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41-51 [doi:10.1007/978-1-4020-6316-9_4](https://doi.org/10.1007/978-1-4020-6316-9_4);
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T. G. G. Battye, L. Kontogiannis, O. Johnson, H. R. Powell and A. G. W. Leslie, "iMOSFLM: a new
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graphical interface for diffraction-image processing with MOSFLM" (2011), Acta Cryst. D67, 271-281
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[doi:10.1107/S0907444910048675](https://doi.org/10.1107/S0907444910048675); H. R. Powell,
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T. G. G. Battye, L. Kontogiannis, O. Johnson and A. G. W. Leslie, "Integrating macromolecular X-ray
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diffraction data with the graphical user interface iMosflm" (2017), Nat. Protoc. 12, 1310-1325
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[doi:10.1038/nprot.2017.037](https://doi.org/10.1038/nprot.2017.037).
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**[CrystFEL](https://www.desy.de/~twhite/crystfel/)** — spot finding, the three-ring integration
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region, the serial/stills processing model, and the per-frame indexing acceptance test
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(`indexing_peak_check()` in `peaks.c`). T. A. White, R. A. Kirian, A. V. Martin, A. Aquila, K. Nass,
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A. Barty and H. N. Chapman, "CrystFEL: a software suite for snapshot serial crystallography" (2012),
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J. Appl. Cryst. 45, 335-341 [doi:10.1107/S0021889812002312](https://doi.org/10.1107/S0021889812002312).
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**[GEMMI](https://github.com/project-gemmi/gemmi)** — symmetry operations, unit-cell and
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structure-factor machinery, and MTZ / XDS_ASCII I/O. Vendored in `gemmi_gph/`, so it also carries a
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licence obligation. M. Wojdyr, "GEMMI: A library for structural biology" (2022), J. Open Source
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Softw. 7, 4200 [doi:10.21105/joss.04200](https://doi.org/10.21105/joss.04200).
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**Hexagonal-ice ring positions** — the eleven measured ring $d$ spacings the ice-ring score, the
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ice-ring flagging and the ice calibrant are all built on are taken from the measurements of, not
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enumerated from a cell. D. W. Moreau, H. Atakisi and R. E. Thorne, "Ice in biomolecular
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cryocrystallography" (2021), Acta Cryst. D77, 540-554
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[doi:10.1107/S2059798321001170](https://doi.org/10.1107/S2059798321001170).
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**Diffraction anisotropy** — the description of the overall fall-off by a single anisotropic
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displacement tensor, its symmetry constraints, and the fact that only its deviatoric part is
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determined (the isotropic part being degenerate with the overall scale) are Sheriff and Hendrickson's.
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The estimator fits that tensor to the observed intensity distribution, taking sigma(I) into account,
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in the sense of Popov and Bourenkov. The directional diffraction limits - <I/sigma(I)> in a cone about
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each principal direction, and the reporting of the anisotropic deltaB as the range of the principal
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components - follow AIMLESS. rugnux reports these; it corrects no intensity and removes no reflection
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on a directional criterion. S. Sheriff and W. A. Hendrickson, "Description of overall anisotropy in
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diffraction from macromolecular crystals" (1987), Acta Cryst. A43, 118-121
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[doi:10.1107/S010876738709977X](https://doi.org/10.1107/S010876738709977X); A. N. Popov and
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G. P. Bourenkov, "Choice of data-collection parameters based on statistic modelling" (2003), Acta
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Cryst. D59, 1145-1153 [doi:10.1107/S0907444903008163](https://doi.org/10.1107/S0907444903008163);
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P. R. Evans and G. N. Murshudov, "How good are my data and what is the resolution?" (2013), Acta
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Cryst. D69, 1204-1214 [doi:10.1107/S0907444913000061](https://doi.org/10.1107/S0907444913000061).
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**Data-quality statistics** follow the established conventions rather than any one program: R_meas
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and R_pim, CC1/2 and CC\*, and the reporting of I/sigma(I). K. Diederichs and P. A. Karplus, "Improved
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R-factors for diffraction data analysis in macromolecular crystallography" (1997), Nat. Struct. Biol.
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4, 269-275 [doi:10.1038/nsb0497-269](https://doi.org/10.1038/nsb0497-269); P. A. Karplus and
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K. Diederichs, "Linking crystallographic model and data quality" (2012), Science 336, 1030-1033
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[doi:10.1126/science.1218231](https://doi.org/10.1126/science.1218231); K. Diederichs and
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P. A. Karplus, "Better models by discarding data?" (2013), Acta Cryst. D69, 1215-1222
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[doi:10.1107/S0907444913001121](https://doi.org/10.1107/S0907444913001121).
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**Uncertainty conventions** follow the IUCr Commission on Crystallographic Nomenclature:
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D. Schwarzenbach, S. C. Abrahams, H. D. Flack et al., "Statistical descriptors in crystallography:
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Report of the IUCr Subcommittee on Statistical Descriptors" (1989), Acta Cryst. A45, 63-75
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[doi:10.1107/S0108767388009596](https://doi.org/10.1107/S0108767388009596); D. Schwarzenbach,
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S. C. Abrahams, H. D. Flack, E. Prince and A. J. C. Wilson, "Statistical descriptors in
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crystallography. II. Report of a Working Group on Expression of Uncertainty in Measurement" (1995),
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Acta Cryst. A51, 565-569 [doi:10.1107/S0108767395002340](https://doi.org/10.1107/S0108767395002340).
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