fullseye

smooth_funct_1d_mean — ONED function op

使い方

Iterated moving-average smoothing (HALCON smooth_funct_1d_mean).

Applies a length-size uniform (box) filter iterations times with nearest (edge-replicating) boundary handling. Repeated box filtering approaches a Gaussian (central limit theorem).

:param y: 1-D function, at least 1 sample. :param size: window length in samples; truncated to int, must be >= 1. Even sizes are accepted but shift the window origin by half a sample (scipy’s origin convention) — prefer odd sizes for a symmetric window. :param iterations: number of passes; truncated to int, must be >= 0. iterations=0 returns the (float64-coerced) input unchanged. :returns: smoothed float64 array, same length as y. :raises ValueError: non-1-D / NaN / Inf input, empty input, size < 1, or iterations < 0.

参考(サンプルデータ・文献)

実行できる例(この op を実際に呼ぶ検証済みサンプル)

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 · derivate_funct_1d · integrate_funct_1d · zero_crossings_funct_1d · local_min_max_funct_1d · abs_funct_1d

同カテゴリ(function)

create_funct_1d_array · create_funct_1d_pairs · smooth_funct_1d_gauss · derivate_funct_1d · integrate_funct_1d · zero_crossings_funct_1d · local_min_max_funct_1d · abs_funct_1d


Provenance: funct1d.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.