check op• 数据种类:calresult → calresult
• 调用: import fullseye as fs; fs.ledger.simcal_discrepancy(result=None, level=0.99) -> 'dict'(要直接调用实现,import simcalcheck; simcalcheck.simcal_discrepancy(result=None, level=0.99) -> 'dict';从台账取用则 opssimcal.get("simcal_discrepancy"))
噪声归一化的残差中是否存在模型无法产生的结构（模型偏差）？
> 以下的详细说明为原文 —— 摘要与标题已翻译。
The residual of every valid pixel is divided by the noise standard deviation (camera noise plus the model's own sample variance), so white residuals have unit variance. With three or more conditions the matrix is conditions x pixels valid in all of them; with fewer it is the rows x columns of the (first) residual image (a smooth spatial pattern is low-rank there). sensitivity.mv_residual_pca counts the components whose singular value exceeds the Tracy-Widom level point of white noise of that shape (Johnstone 2001; level in 0.90 / 0.95 / 0.99 — the bare Marchenko-Pastur edge sqrt(n) + sqrt(p) is exceeded by pure noise 10-14 % of the time, measured). Structure found: verdict = "structure", the loadings as maps (where the model is wrong), and a warning that every uncertainty of the result is optimistic — a calibrated knob may be absorbing the missing physics.
• 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_pocket_interreflection — py -3.11 examples/poc_pocket_interreflection.py
• poc_simcal_thin_film — py -3.11 examples/poc_simcal_thin_film.py
• simcal_checks_tour — py -3.11 examples/simcal_checks_tour.py
calresult 作为输入)simcal_identifiability · simcal_uncertainty · simcal_validate · simcal_report
check)simcal_identifiability · simcal_uncertainty · simcal_validate
*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.