* simurg/core/brand.py: single source of the mark geometry, colours, favicon
and the report header band (scripts/brand now load it from there).
* HTML reports (QC report, compare dashboard, methylation QC): offline SVG
favicon, indigo header band with the mark, version and a sha256 of the data
shown; Noto Sans font stack; methylation plots in Okabe-Ito colours.
* README banner, guide logo, brand/blog links; branding brief updated to the
final identity; Noto (OFL) and Okabe-Ito entries in THIRD_PARTY_NOTICES;
CHANGELOG (Unreleased).
Unit tests + P5 QC oracle: 285 passed; ruff and mypy clean.
User guide: ArrayTrain section, v2 commands in the table, v2 accuracy rows,
updated limitations. README status for v2.0.0. Version 2.0.0 (Python package);
the Rust kernels are unchanged and stay simurg_core 1.1.0. uv.lock committed
(uv lock --check clean).
Full suite on the Pi, file by file under the memory guard: 29 files exit 0
(unit: 282 passed), ruff and mypy clean.
Fixed θ windows mislabelled compressed/asymmetric loci (2-cluster loci: 1418 vs
186 errors). Now 1/2/3-component mixtures chosen by BIC, labelled by HWE
goodness of fit plus weak position and gap priors, split clusters merged.
GSE165845 chr22 vs 1000G 30x (240 arrays): concordance 99.44 % (v1 99.27 %,
vendor EGT 99.46 %), NRD 1.30 % (1.89 %, 1.23 %), call rate 99.61 %.
docs/validation/V2_arraytrain.md, K-030; plan §12, CLI-038.
beta r 0.99998 vs sesame 1.28.1 (max |dbeta| 0.011), detection calls 99.1% identical,
noob within 0.5% median; replicate r 0.997; all 21 control metrics pass. Spec deviations
recorded (5-field control lines, pOOBAH formula, minfi sheet keys). User guide section.
Wheels (pure + manylinux_2_28 kernels), sdist, Docker image and conda packages built and
installed on fresh Ubuntu 24.04 machines; 225 unit tests pass against the installed
package; the tutorial runs with pip (with and without kernels); GTC/VCF content digests are
identical across pip, Docker and conda on both architectures and equal to the Pi's run.
docs/validation/P10.md; guide: install from wheels, Docker, conda; exit code 141.
Graviton3 c7g.8xlarge, 360 GSE165845 arrays: 360/360 GTCs identical between the Rust
kernels and the pure-Python paths; 1 worker 78-80 samples/min (pure Python 29.6).
Scaling 1->8 workers efficiency 0.87-0.90; above that the 125 MB/s gp3 disk caps the
run (~620 samples/min) and, on a RAM disk, a fixed per-worker start-up cost limits a
360-sample batch to efficiency 0.48 at 32 workers (K-025). Worker state is pickled once.
docs/validation/P9.md, result JSONs, guide/README/CHANGELOG updates.
docs/user_guide.md (install, inputs, complete run, commands, presets, QC, outputs,
accuracy, limitations, troubleshooting), examples/gsa_demo.sh (end-to-end run on the
public GSA demo, verified on the Pi), examples/sample_sheet.csv, CHANGELOG.md; version 1.0.0.
kemal