variation op• 資料種類:無 → table(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.varmodel_band_k(n=20, far=0.001, spread='std', df_prior=None)(要直接呼叫實作,import varmodel; varmodel.varmodel_band_k(n=20, far=0.001, spread='std', df_prior=None);從台帳取用則 opsspc.get("varmodel_band_k"))
對應所宣告的每像素雙側誤檢率的容許帶半寬 k(以離散度為單位,table)。
> 以下的詳細說明為原文 —— 摘要與標題已翻譯。
A new good pixel x is flagged when |x - center| > k * spread. Under per-pixel independent normal good samples:
• std: (x - mean)/(s * sqrt(1+1/n)) ~ t_{n-1} so k = t_{n-1}^-1(1 - far/2) * sqrt(1+1/n).
• pooled: one variance pooled over many pixels (degrees of freedom df_prior; None = infinite) → normal quantile.
• moderated: empirical-Bayes shrunk variance with df_prior = d0 prior degrees of freedom (Smyth 2004) → t_{n-1+d0}.
• mad: median / MAD centre and spread → no closed form, but the ratio is a pivot, so k is a Monte-Carlo quantile that depends on (n, far) only (fixed seed; mc_far_rel_se is the relative standard error of the achieved rate). Needs n >= 5 and far >= 1e-3.
The threshold comes from the distribution, never from test defects. Returns k, df (0 for mad: no t quantile is involved), far, n, spread, source, mc_far_rel_se.
Raises ValueError for n < 2 (mad: n < 5), far outside [1e-9, 0.5), an unknown spread or a non-positive df_prior.
• 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。
• (尚無)
table 作為輸入)msa_anova_table · msa_gauge_rr · msa_bias_linearity · msa_attribute_agreement · gum_standard_uncertainty · gum_propagate · gum_expanded · gum_monte_carlo
variation)varmodel_alignment · varmodel_fit · varmodel_calibrate · varmodel_score
*Provenance: varmodel.py — SPC 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.