sensitivity op• 数据种类:design × signal → table
• 调用: import fullseye as fs; fs.ledger.sens_morris(design=None, y=None, negligible=0.05) -> 'dict'(要直接调用实现,import sensitivity; sensitivity.sens_morris(design=None, y=None, negligible=0.05) -> 'dict';从台账取用则 opsmultivar.get("sens_morris"))
Morris 基本效应 -> 各因子的 mu、mu*、sigma（Morris 1991；mu* 见 Campolongo 等 2007）。
> 以下的详细说明为原文 —— 摘要与标题已翻译。
design must come from doe_morris (its trajectory bookkeeping is used) and y holds the model output for its rows in order. For trajectory t and step s that moves factor i by ±delta: EE_i = (y_s - y_{s-1}) / (±delta) in unit-cube units, and also per natural unit of the factor (ee_natural; on a log-scale factor the step is in log10 units).
mu (mean EE) can cancel when effects change sign; mu_star (mean |EE|) does not and is the ranking measure; sigma (standard deviation, ddof = 1) is large when the effect depends on where the other factors are (non-linear or interacting). class per factor: negligible (mu* below negligible x the largest mu*), linear/additive (sigma < 0.1 mu*: the effect is the same everywhere — a convention of this op, stated), otherwise non-linear or interacting.
• 示例数据目录(下载 URL / 许可证) —— 2-D 用 skimage.data(BSD/公有领域)加合成图,3-D 给出真实数据源(Stanford/PDS 等)的下载 URL。
• 算子来历与参考文献 —— 该算子族所依据的研究/方法出处。
• 算法的正典(作者、年份)与用途见上面的族使用指南。
• sensitivity_tour — py -3.11 examples/sensitivity_tour.py
table 作为输入)—
sensitivity)doe_morris · doe_saltelli · sens_sobol
*Provenance: sensitivity.py — MULTIVAR 算子登记表。本条目由 tools/opdocs.py md 自动生成(请勿手工编辑)。*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.