fullseye

spc_mt_sn_ratio — SPC mt op

• データ種: signal → table
• 呼び出し: import fullseye as fs; fs.ledger.spc_mt_sn_ratio(md) (実装を直接呼ぶなら import spc; spc.spc_mt_sn_ratio(md)、台帳から引くなら opsspc.get("spc_mt_sn_ratio"))

使い方

Larger-the-better SN ratio of abnormal-sample distances, in decibels.

MT-method item selection asks which features earn their place: run the unit space with a subset of features, score the abnormal samples, and keep the subset whose distances are largest. The figure of merit is the larger-the-better signal-to-noise ratio

eta = -10 log10( (1/n) sum_i 1 / MD_i^2 )

an inverse-square average, so one abnormal sample that the subset fails to separate drags the whole score down — which is the behaviour wanted when the cost of a miss dominates. The caller drives the subsets (classically by an orthogonal array); this operator is the closed-form score for one subset.

md is a 1-D array of distances for the abnormal samples. Returns a dict with sn_ratio_db, the harmonic_mean_md_sq it came from, and n.

For a constant MD == d the sum collapses and eta == 20 log10(d) exactly — pinned in the tests, and the reason a subset that puts every abnormal sample at distance 10 scores exactly 20 dB.

Raises ValueError: an empty or non-1-D md, a non-positive entry (a zero distance would divide by zero: an abnormal sample sitting exactly on the unit-space centre means the subset separates nothing), or non-finite input.

参考(サンプルデータ・文献)

• サンプルデータ カタログ(DL URL / ライセンス) — 2-D は skimage.data(BSD/public)+ 合成、3-D は実データ源(Stanford/PDS 等)の DL URL。
• 演算子の来歴・参考文献 — この op 族の元になった研究/手法の出典。
• アルゴリズムの正典(著者・年)と用途は上記ファミリ使い方ガイドに記載。

実行できる例(この op を実際に呼ぶ検証済みサンプル)

• poc_spc — py -3.11 examples/poc_spc.py

型が繋がる次の op(table を入力に取れる)

msa_anova_table · msa_gauge_rr · msa_bias_linearity · msa_attribute_agreement · gum_standard_uncertainty · gum_propagate · gum_expanded · gum_monte_carlo

同カテゴリ(mt)

spc_mt_unit_space · spc_mt_distance

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Provenance: spc.py — SPC operator registry. この per-op ノートは tools/opdocs.py md が自動生成(手編集しない)。

© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.

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