plan op• Data kinds: none → design (an op determined by its arguments alone — it takes no image or data input)
• Call: import fullseye as fs; fs.ledger.doe_orthogonal_array(name='L9', factors=None, columns=None) -> 'dict' (to call the implementation directly, import doe; doe.doe_orthogonal_array(name='L9', factors=None, columns=None) -> 'dict'; from the registry, opsmultivar.get("doe_orthogonal_array"))
Orthogonal array L4 / L8 / L9 / L12 / L16 / L18 / L27 from a published table -> design.
The arrays are copied from published tables (sources and the copy check in OA_SOURCES), not generated: Taguchi's numbering of columns is what shop-floor literature and the linear graphs refer to, and a generated array with another column order would silently assign factors to interaction columns. Published level symbols 1, 2 (, 3) map to coded −1, +1 (, or −1, 0, +1).
factors: int / names / (name, lo, hi[, unit[, scale]]) (default: one factor per column). columns: 1-based column numbers to assign the factors to, in order (default: the first k columns; for L18 column 1 is the two-level one).
The returned alias lists, for every pair of assigned factors, the columns their interaction falls on and the share (see _oa_interaction_share) — if such a column also carries an assigned factor, that main effect is confounded with the interaction. meta['strength2_ok'] re-checks orthogonality on the table actually used, and meta['regular'] says whether interactions land on whole columns.
• 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.
• doe_plan_tour — py -3.11 examples/doe_plan_tour.py
• multivar_inspection_tour — py -3.11 examples/multivar_inspection_tour.py
• poc_simcal_thin_film — py -3.11 examples/poc_simcal_thin_film.py
design as input)doe_decode · rsm_fit · doe_main_effects · sens_morris · sens_sobol
plan)doe_lhs · doe_fractional_factorial · doe_central_composite · doe_box_behnken
*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.