coding op• Data kinds: matrix → design
• Call: import fullseye as fs; fs.ledger.doe_encode(natural=None, factors=None) -> 'dict' (to call the implementation directly, import doe; doe.doe_encode(natural=None, factors=None) -> 'dict'; from the registry, opsmultivar.get("doe_encode"))
Natural-unit settings (n, k) -> design with coded values (−1..+1 = lo..hi).
Use it to bring runs that were *not* planned here (a historical log, a hand-made plan) into the same coded frame the analysis ops read. factors gives the ranges (and per-factor "log" scale: coded = position of log10(x) between log10(lo) and log10(hi)). Values outside lo..hi are kept (coded beyond ±1) and named in meta['outside_range'].
• design_of_experiments family guide
• Sample-data catalog (download URLs / licences) — 2-D uses skimage.data (BSD/public domain) plus synthetic images; 3-D lists download URLs for real data sources (Stanford, PDS, …).
• Operator provenance and references — the sources of the research/methods this op family came from.
• The canonical algorithm (author, year) and its uses are named in the family usage guide above.
• multivar_inspection_tour — py -3.11 examples/multivar_inspection_tour.py
design as input)doe_decode · rsm_fit · doe_main_effects · sens_morris · sens_sobol
coding)*Provenance: doe.py — MULTIVAR operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.