doe_decode — MULTIVAR coding op

• Data kinds: design → matrix

• Call: import fullseye as fs; fs.ledger.doe_decode(design=None, coded=None) -> 'np.ndarray' (to call the implementation directly, import doe; doe.doe_decode(design=None, coded=None) -> 'np.ndarray'; from the registry, opsmultivar.get("doe_decode"))

Usage

design -> natural-unit matrix (n, k); or decode any coded point(s) with its ranges.

coded=None returns the design's natural matrix recomputed from its coded matrix (so a hand-edited natural cannot drift from coded). Pass coded (k,) or (m, k) — e.g. a stationary point from multivar.rsm_fit — to map it to bench settings with the same ranges and scales.

Detailed usage guide

• design_of_experiments family guide

References (sample data, literature)

• 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.

Runnable examples (verified samples that actually call this op)

• 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

• sensitivity_tour — py -3.11 examples/sensitivity_tour.py

Ops the type connects to (they accept matrix as input)

doe_encode · mv_pca · mv_pls · mv_confounding · mv_residual_pca

Same category (coding)

doe_encode

*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.