tb_smooth_funct_1d_mean — 2D typed op

• 数据种类:signal → signal

• 调用:fullseye.apply(img, "tb_smooth_funct_1d_mean", a=0.5, b=0.5)(2-D 的模型是一张图 + 两个标量旋钮 a,b∈[0,1])

用法

迭代式移动平均平滑(HALCON `smooth_funct_1d_mean`)。

> 以下的详细说明为原文 —— 摘要与标题已翻译。

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`.

Typed bridge of the 1d op `smooth_funct_1d_mean into the 2-D evolution registry: the same implementation, called under the op(v, a, b) convention. a drives size (default 3) and b drives iterations` (default 1).

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。

可运行的示例(实际调用该算子并已验证的样例)

• (暂无)

类型可衔接的下一个算子(可接受 signal 作为输入)

identity · tb_create_funct_1d_array · tb_smooth_funct_1d_gauss · tb_derivate_funct_1d · tb_integrate_funct_1d · tb_zero_crossings_funct_1d · tb_abs_funct_1d · tb_negate_funct_1d

同类别(typed)

tb_points_to_voxel · tb_estimate_point_normals · tb_iss_keypoints · tb_angle_3points · tb_project_points · tb_render_point_depth · tb_statistical_outlier_removal · tb_radius_outlier_removal

*Provenance: ops.py — 2D 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.