sensitivity op• 資料種類:無 → design(僅由參數決定的運算子 —— 不接受影像或資料輸入)
• 呼叫: import fullseye as fs; fs.ledger.doe_saltelli(n=1024, factors=3, seed=0) -> 'dict'(要直接呼叫實作,import sensitivity; sensitivity.doe_saltelli(n=1024, factors=3, seed=0) -> 'dict';從台帳取用則 opsmultivar.get("doe_saltelli"))
用於 Sobol' 指數的樣本矩陣(Saltelli 等 2010)-> 共 n (k + 2) 次執行的 design。
> 以下的詳細說明為原文 —— 摘要與標題已翻譯。
A Sobol' sequence of dimension 2k gives two independent n x k matrices A (first k columns) and B (last k). For each factor i, A_B^(i) is A with column i taken from B. Rows are stacked as [A; B; A_B^(1); ...; A_B^(k)] (meta['blocks']), which is the layout sens_sobol reads.
n must be a power of two: the balance properties of a Sobol' sequence hold for 2^m points, and the estimators' error behaves erratically otherwise — the op refuses rather than silently degrading. seed scrambles the sequence (Owen scrambling via scipy); seed=None uses the plain sequence.
• 範例資料目錄(下載 URL / 授權) —— 2-D 用 skimage.data(BSD/公有領域)加合成圖,3-D 給出真實資料源(Stanford/PDS 等)的下載 URL。
• 運算子來歷與參考文獻 —— 該運算子族所依據的研究/方法出處。
• 演算法的正典(作者、年份)與用途見上面的族使用指南。
• sensitivity_tour — py -3.11 examples/sensitivity_tour.py
design 作為輸入)doe_decode · rsm_fit · doe_main_effects · sens_morris · sens_sobol
sensitivity)doe_morris · sens_morris · sens_sobol
*Provenance: sensitivity.py — MULTIVAR 運算子登記表。本條目由 tools/opdocs.py md 自動產生(請勿手動編輯)。*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.