spc_mt_distance — SPC mt op

• 数据种类:matrix → table

• 调用: import fullseye as fs; fs.ledger.spc_mt_distance(data, mean=None, std=None, inv_corr=None, threshold=3.0)(要直接调用实现,import spc; spc.spc_mt_distance(data, mean=None, std=None, inv_corr=None, threshold=3.0);从台账取用则 opsspc.get("spc_mt_distance"))

用法

> 该算子的说明尚无译文,以下照原文给出。

Score observations against an MT-method unit space.

data is a 2-D array of shape (m, p). Pass the mean, std and inv_corr from spc_mt_unit_space to score new product against a stored unit space; omit all three and the unit space is built from data itself, which is the training case and makes md_sq_mean land on (m-1)/m.

Each row's distance is MD_i = sqrt(z_i' R^-1 z_i / p) with z_i = (x_i - mean) / std. Rows with MD > threshold are reported in flagged; the rest in inside. Dividing the quadratic form by p is what puts the unit space at 1 regardless of how many features are used, so a threshold carries over when features are added or removed.

Returns a dict with the per-row md and md_sq arrays, flagged, inside, the threshold, md_sq_mean, and n/p.

Relationship to spc_hotelling_t2 (used as the oracle in the tests):

on the standardised matrix the covariance *is* the correlation, so md**2 == t2 / p exactly for the same data.

Raises ValueError: a non-2-D / empty *data*, a non-positive threshold, a unit space given only in part, a mean / std / inv_corr whose shape disagrees with p, a non-positive entry in std, or non-finite input.

参考(示例数据、文献)

• 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。

可运行的示例(实际调用该算子并已验证的样例)

• poc_mt_hidden_fault — py -3.11 examples/poc_mt_hidden_fault.py

• poc_spc — py -3.11 examples/poc_spc.py

类型可衔接的下一个算子(可接受 table 作为输入)

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

同类别(mt)

spc_mt_unit_space · spc_mt_sn_ratio


*Provenance: spc.py — SPC 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.