Cartridge genotype plane: persist population genotype priors on a cartridge - #7
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…normalizer, allow_nonfunctional bool)
…py carried novels
…ne subject check, order-independent draws
… round) - from_genotypes: validate pseudocount (finite >=0, reject bool); reject unknown carried alleles; reject copy_count>1 single-entry slots; validate model before return - Genotype.sample: validate a directly-attached plane before use - manifest: report genotype_priors 'valid' flag, never leak NaN numerics - to_metadata: add effective_refdata_hash for carried-novel genotypes
…nd 2) - manifest: never crash on a garbage/invalid direct-attached plane (type-check, guard content_checksum/float, defensive dict access) - Genotype.sample: require use_cartridge_priors to be a real bool - from_genotypes: require include_novel bool; validate min_subjects (int>=1) and segments (non-empty unique V/D/J labels present in cfg; reject bare string)
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Summary
Adds a donor-population germline prior ("population genotype model") as a top-level cartridge plane (
DataConfig.genotype_priors), soGenotype.sample(cfg)can draw per-individual genotypes from a cartridge-authored prior instead of a uniform synthetic one. Follow-on #2 of the genotype roadmap (after V1 #5 and population priors #6).Python-only — zero
engine_rs/changes. The plane is consumed entirely inGenotype.sample, which already lowers a fully-specified genotype through the existingSampleGenotypePass; population novel alleles reuse the existing effective-refdata injection. NoExperimentAPI change.What's included
genotype_priors.py—PopulationGenotypeModel+PopulationNovelAllele: per-segment/gene allele frequencies, per-gene haplotype-deletion probabilities, chromosome weights, population novel alleles, and identity (model_id/source/version/description). Catalogue-freevalidate()(shape, numeric bounds, DNA, ChainType-normalized D-on-VJ rejection) + canonicalcontent_checksum().PopulationGenotypeModel.from_genotypes(...)— pure estimator from observedGenotypes: per-chromosome allele counts (homozygous=2 / hemizygous=1), deletion prob =deleted_haplotypes / (2·n_subjects), pseudocount on catalogue alleles only, with completeness / copy-number / subject-id / input-type guards.DataConfig.genotype_priors— fifth top-level plane; legacy-pickle fallback; None-pop checksum shim (unused plane → byte-identical cartridge checksum; a real plane → distinct identity);models.genotype_priorsmanifest block (robust against malformed direct-attached planes).Genotype.sample— per-input source resolution withuse_cartridge_priorsopt-out; candidate-vs-carried novel injection (include_cartridge_novel_alleles); genotype-levelprior_provenance+to_metadata()(base + effective refdata hashes); order-independent draws.set_genotype_priors(catalogue-aware + functional novel validation) and chainableestimate_genotype_priors.Invariants
compute_checksum(); a real plane is part of cartridge identity.effective_dataconfig()/ AIRR projection — uncarried candidates never leak.Test plan
tests/test_genotype_cartridge_plane.py(45 tests): validation, checksum invariant + canonicality, serialization round-trip, manifest, sampler provenance/opt-out/mixed-sourcing, candidate-vs-carried novel injection, estimator statistics + guards, builder set/estimate, input-type hardening, end-to-end truth-call carriage.engine_rs/changes (compiled engine byte-identical).