mt op• 資料種類:matrix → table
• 呼叫: import fullseye as fs; fs.ledger.spc_mt_distance(data, mean=None, std=None, inv_corr=None, threshold=3.0)(要直接呼叫實作,import spc; spc.spc_mt_distance(data, mean=None, std=None, inv_corr=None, threshold=3.0);從台帳取用則 opsspc.get("spc_mt_distance"))
> 該運算子的說明尚無譯文,以下照原文給出。
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 :func: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 :func: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.
• 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_mt_hidden_fault — py -3.11 examples/poc_mt_hidden_fault.py
• poc_spc — py -3.11 examples/poc_spc.py
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
mt)spc_mt_unit_space · spc_mt_sn_ratio
*Provenance: spc.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.