spc_xbar_r — SPC chart op

• 資料種類:matrix → table

• 呼叫: import fullseye as fs; fs.ledger.spc_xbar_r(subgroups)(要直接呼叫實作,import spc; spc.spc_xbar_r(subgroups);從台帳取用則 opsspc.get("spc_xbar_r"))

用法

> 該運算子的說明尚無譯文,以下照原文給出。

Shewhart Xbar-R control chart from subgroup measurements.

`subgroups is a 2-D array of shape (m, n) — m subgroups of n`

measurements each, `2 <= n <= 10` (the range chart is only calibrated for

small subgroups). For each subgroup `j` the plotted statistics are the mean

`Xbar_j and the range R_j = max - min`. The centre lines are the grand

mean `Xbarbar and the mean range Rbar`, and with the ISO 8258 constants

`(A2, D3, D4) for that n`::

xbar_ucl = Xbarbar + A2*Rbar xbar_lcl = Xbarbar - A2*Rbar

r_ucl = D4*Rbar r_lcl = D3*Rbar

Returns a dict (a "table") with the per-subgroup `xbar / r` arrays, the

six limits and three centre lines, the integer indices `out_of_control` of

subgroups outside either chart, and `in_control` (True when that list is

empty). The constants are fixed by `n: for n=5` they are exactly

`A2=0.577, D3=0.000, D4=2.115` (pinned in the tests).

Raises `ValueError`: a non-2-D / empty *subgroups*, a subgroup size

outside `[2, 10]`, or non-finite / mislabelled input.

參考(範例資料・文獻)

• 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。

可執行的範例(實際呼叫該運算子並已驗證的樣例)

• poc_spc — py -3.11 examples/poc_spc.py

型別可銜接的下一個運算子(可接受 table 作為輸入)

—

同類別(chart)

—

*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.