Found by the P10 fresh-VM run: `simurg inspect … | head` raised BrokenPipeError, reported as
an internal error, and stopped examples/gsa_demo.sh (set -o pipefail). run_guarded now flushes
stdout inside the guard and maps BrokenPipeError to ExitCode.SIGPIPE (141) without a message.
p10.sh: SKIP_DOCKER/SKIP_CONDA, clearer digest report; p10t.sh runs build+pip+tutorial only.
Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01814GKVzZVL3FuF3DeiZXhv
scripts/build_dist.sh: sdist + pure wheel + manylinux_2_28 kernel wheels (maturin --zig,
both architectures). Dockerfile (multi-stage, kernels included, non-root user).
packaging/conda/{simurg,simurg-core}. scripts/p10/digest.py: platform-independent content
digests of GTC/VCF/summary outputs. Cloud task p10 installs the artifacts on a fresh
Ubuntu VM and runs the tutorial with pip, Docker and conda installs. trial.sh picks the
arm64/amd64 image from the instance type and can run instances in parallel (PARALLEL=1).
Licence files ship in both wheels; Rust crate notices added.
Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01814GKVzZVL3FuF3DeiZXhv
Rust ports of the hot paths found by profiling: fused per-locus GenCall calling
and scoring, BAF/LRR, libm maps with CPython math semantics, both nearest-neighbour
searches of the normalization fit, and the BPM LocusEntry parser. Address
coverage is memoised per IDAT layout. SIMURG_PURE_PYTHON=1 forces the pure paths.
On the Pi: genotype_sample 3.4 s -> 1.1 s, 36-sample GSA run 131 s -> 46 s, BPM
read 4x faster; 36 GSA + 6 Omni2.5 GTCs and QC tables byte-identical to the pure
path; tests/unit/test_core_kernels.py checks every kernel on edge cases.
bench/profile_genotype.py, bench/scaling.py, cloud task p9 (thread scaling).
Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01814GKVzZVL3FuF3DeiZXhv
The download-only phase (EBI ~15 MB/s) left the CPU idle long enough for the
idle alarm to terminate the first run. Streams are now cut to the manifest
positions (±100 bp) and the 120 individuals while genotyping runs.
Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01814GKVzZVL3FuF3DeiZXhv
scripts/p8/prepare.py lays out the 360 GEO IDATs under their header barcode/position;
scripts/p8/validate_p8.py computes concordance, NRD, no-call rate, per-class and per-MAF
sensitivity/specificity/precision/F1 vs NYGC 30x and GIAB HG001, replicate concordance,
systematic/allele-swap site errors, per-chip batch table and duplicate detection.
Cloud userdata can skip the Omni2.5 archive (OMNI=0).
Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01814GKVzZVL3FuF3DeiZXhv
- tests/unit/test_genotype.py: fuzzy memberships incl. NaN rules, calls
at cluster centres, intensity threshold, BAF/LRR interpolation and
NaN pattern, LogR-dev locus set, sex rules v1/v2, TOP-strand base
calls, invariant dates, end-to-end `simurg genotype` (summary schema,
pass-through columns, thread/layout determinism, overwrite refusal)
- tests/oracle/test_p4_genotype.py: 36 GSA samples x 2 versions
byte-identical to the oracle
- scripts/validate_p4_large.py + cloud task p4: compare every vendor
GTC field by field and as whole files; reports which sex rule matches
Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01814GKVzZVL3FuF3DeiZXhv
- fit.py: exact and binned nearest-neighbour searches use one distance
matrix per searched bin (first-minimum rule kept); fit 2.6 s -> 1.4 s
per GSA sample, still bit-identical to the oracle
- scripts/validate_p3_large.py: refits 1.2.0 and 1.1.2 transforms for
every vendor GTC and reports ULP distances per field
- cloud trial runs scripts/cloud/tasks/<TASK>.sh (TASK=p3 default;
p1p2 = previous validation + ingest)
Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01814GKVzZVL3FuF3DeiZXhv
- tests/oracle/test_p2_raw_xy.py: IDAT-assembled raw X/Y and controls
equal the arrays in oracle GTCs
- validate_p1_large.py: phase-P2 comparison against vendor GTCs with
diagnostics (channel swap, bead-count disagreements)
- cloud trial: also runs `simurg ingest` on all samples (time/memory),
disk 250 GB
Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01814GKVzZVL3FuF3DeiZXhv
scripts/cloud/trial.sh launches one spot instance that validates the
parsers on the 1000 Genomes Omni2.5 set (2141 samples, vendor GTCs)
streamed from the public S3 bucket, uploads the summary and terminates
itself. Cost guards: spot price cap, hard time limit (shutdown =
terminate), EXIT-trap shutdown, CloudWatch idle alarm that terminates
from outside, disk deleted with the instance, monthly budget alert, and
an `audit` command listing anything still billable.
scripts/validate_p1_large.py compares every GTC with BeadArrayFiles,
checks byte-identical round-trips, IDAT pairs and BPM/EGT/CSV.
Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01814GKVzZVL3FuF3DeiZXhv
kemalandClaude Opus 5.5