Add unified prediction model (Pred, PeptidePreds, MultiSample) - #177
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New data model with self-contained Pred objects, PeptidePreds grouping
with best_affinity/best_presentation/best_stability helpers, and
MultiSample for running across patients with different HLA genotypes.
New API:
- predictor.predict(peptides) -> list[PeptidePreds]
- predictor.predict_proteins(seq_dict) -> {name: list[PeptidePreds]}
- predictor.predict_dataframe() / predict_proteins_dataframe()
- MultiSample(samples={name: alleles}, predictor_class=...) wrapper
Header-driven parser (parse_netmhcpan_to_preds) returns Pred objects
natively. NetMHCpan 4.1 emits both pMHC_affinity and pMHC_presentation
per peptide-allele pair.
Full backward compatibility: BindingPrediction, predict_peptides(),
predict_subsequences() all still work. Conversion bridge via
to_pred()/from_pred()/to_peptide_preds().
Replace pylint (crashing on modern type annotations) with ruff. Fix pre-existing issues: bare excepts, ambiguous variable names, unused imports, None comparisons, type() comparisons.
Add NetMHCpan42/NetMHCpan42_BA/NetMHCpan42_EL classes (same output format as 4.1). Rewrite NetMHCpan factory to parse the version string and look up in a version map. Unknown versions >= 4.1 fall back to the latest known class with the header-driven auto-detecting parser instead of crashing.
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Summary
Pred(frozen, self-contained),PeptidePreds(best_* helpers),Kindenum, andMultiSample(multi-patient wrapper)predict()→list[PeptidePreds],predict_proteins()→{name: list[PeptidePreds]}, both with_dataframevariantsparse_netmhcpan_to_preds()returnsPredobjects natively; NetMHCpan 4.1 emits both affinity and presentation per rowBindingPrediction,predict_peptides(),predict_subsequences()unchanged, withto_pred()/from_pred()bridgeTest plan