check op• 資料種類:calresult → calresult
• 呼叫: import fullseye as fs; fs.ledger.simcal_discrepancy(result=None, level=0.99) -> 'dict'(要直接呼叫實作,import simcalcheck; simcalcheck.simcal_discrepancy(result=None, level=0.99) -> 'dict';從台帳取用則 opssimcal.get("simcal_discrepancy"))
雜訊正規化的殘差中是否存在模型無法產生的結構（模型偏差）？
> 以下的詳細說明為原文 —— 摘要與標題已翻譯。
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
• 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。
• 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 作為輸入)simcal_identifiability · simcal_uncertainty · simcal_validate · simcal_report
check)simcal_identifiability · simcal_uncertainty · simcal_validate
*Provenance: simcalcheck.py — SIMCAL 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.