check op• 数据种类:calresult → calresult
• 调用: import fullseye as fs; fs.ledger.simcal_uncertainty(result=None, method='laplace', n_boot=40, level=0.95, seed=0) -> 'dict'(要直接调用实现,import simcalcheck; simcalcheck.simcal_uncertainty(result=None, method='laplace', n_boot=40, level=0.95, seed=0) -> 'dict';从台账取用则 opssimcal.get("simcal_uncertainty"))
已确定旋钮的标准差与区间：Laplace（Fisher 信息之逆）或参数自助法。
> 以下的详细说明为原文 —— 摘要与标题已翻译。
Only knobs that kept a point estimate are covered; knobs without one are held at the end point (the intervals are conditional on them — stated in note). laplace: covariance = inverse of J^T W J at the estimate on the unit-scaled knobs, intervals u ± z sd mapped back through each knob's scale (a log knob gets an asymmetric interval), std by the delta method. bootstrap: n_boot refits to the fitted prediction plus Gaussian noise of the noise model's variance (Efron 1979), percentile intervals at level. A result with no point estimate is refused. Under a model discrepancy both are optimistic (simcal_discrepancy says so).
• sim_to_real_calibration 族使用指南
• 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。
• poc_simcal_thin_film — py -3.11 examples/poc_simcal_thin_film.py
calresult 作为输入)simcal_identifiability · simcal_validate · simcal_discrepancy · simcal_report
check)simcal_identifiability · simcal_validate · simcal_discrepancy
*Provenance: simcalcheck.py — SIMCAL 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.