tb_smooth_funct_1d_mean — 2D typed op

• Data kinds: signal → signal

• Call: fullseye.apply(img, "tb_smooth_funct_1d_mean", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])

*No figure: this op takes signal as input. A Studio program starting from an image cannot reach that type — see the runnable examples below for how it is used.*

Usage

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`.

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).

References (sample data, literature)

• Sample-data catalog (download URLs / licences) — 2-D uses skimage.data (BSD/public domain) plus synthetic images; 3-D lists download URLs for real data sources (Stanford, PDS, …).

• Operator provenance and references — the sources of the research/methods this op family came from.

Runnable examples (verified samples that actually call this op)

• (none yet)

Ops the type connects to (they accept signal as input)

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

Same category (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 operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.