local_std — ONED signal op

データ種: signalsignal

呼び出し: import fullseye as fs; fs.ledger.local_std(x, window=9) (実装を直接呼ぶなら import dsp; dsp.local_std(x, window=9)、台帳から引くなら ops1d.get("local_std"))

使い方

Rolling standard deviation with a stated error bound.

The 1-D counterpart of the image operator `local_std` (HALCON's

`deviation_image`): the variance is taken after subtracting the mean

(`E[x^2] - E[x]^2` loses its significant digits on a signal that sits far

from zero), unbiased by `n/(n-1)`, and the residual bias of the square root

removed by `c4(n), so the estimate of sigma` itself is unbiased.

*window* is the number of samples in the sliding window, **rounded up to the

next odd number** so the window can be centred (10 becomes 11). The error

bound below is computed from the window actually used, so the number quoted

stays true. The 2-D side does the same thing — `_k(a)` snaps the knob to

3/5/7/9 — and the typed bridge that exposes this op as `tb_local_std`

scales the knob continuously, so an even value arrives whenever the knob

lands between two odd ones.

**The relative standard error of each estimate is `1/sqrt(2(n-1))`** —

35 % for a 5-sample window, 11 % for 41. Quote it next to any noise figure:

a rolling sigma over 9 samples is +- 25 %, which is wider than most of the

changes people try to read off it.

Returns an array the same length as *x* (the ends are reflected).

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)

gallery2d_texture_freqpy -3.11 examples/gallery2d_texture_freq.py

型が繋がる次の op(signal を入力に取れる)

create_funct_1d_array · create_funct_1d_pairs · smooth_funct_1d_gauss · smooth_funct_1d_mean · derivate_funct_1d · integrate_funct_1d · zero_crossings_funct_1d · local_min_max_funct_1d

同カテゴリ(signal)

lowpass · highpass · bandpass · envelope · rms · quantize · companding_mu_law · resample


*Provenance: dsp.py — ONED 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.