Backport FT8, K15: recursive-descent GPR pruning; fix stale KEGG cutoff fallbacks#658
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… (FT8) Replace the #n# placeholder loop with a recursive parse-tree walk. OR nodes (isozymes) prune negative-score branches while keeping at least one; AND nodes (complexes) are scored as a unit and pruned only at the enclosing OR level. Nested isozyme groups within a complex are simplified in place. NaN-scored genes/complexes are retained (treated as non-negative).
…aults (K15) Fallback values when empty were still the old 1e-50 and 0.8; align them with the parseRAVENargs defaults of 1e-30 and 0.9.
Function test results206 tests 185 ✅ 25s ⏱️ Results for commit bfea22a. |
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Summary
removeLowScoreGenes.m): RewriteprocessComplexRulewith a recursive parse-tree walk, replacing the iterative#n#placeholder approach.G1 & (G2 | G3) & G4) are simplified in place — the old regex approach could not handle these correctly.getKEGGModelForOrganism.m): Fix stale fallback values forcutOff(1e-50→1e-30) andminScoreRatioG(0.8→0.9) when callers explicitly pass an empty value. Aligns them with theparseRAVENargsdefaults set in Backport FS1/FS2/FS4, H1/H4, FT8: correlation-based FSEOF, homology strictness split, deterministic tie-break #655.KEGG pipeline status
Most KEGG items (K1–K3, K6, K7, K12, K14) are already resolved in MATLAB: K1–K3 moved to the Python-generated
keggModel.matartefact; K7 (singlehmmsearch) and K14 sorting/gzip are done in the existing code. K15 cutoff recalibration was done in the defaults by a prior PR; this commit fixes only the dead fallback paths.Test plan
processComplexRuledocstring examples hold:G1 | (G2 and G3 and G4),G1 | (G2 and G3) | (G4 and G5),(G1 and (G2 or G3) and G4)— each with the stated negative genes — produces the stated output.G1 | G2 | G3) and simple complex rules (G1 & G2) are unchanged (they bypassprocessComplexRule).