smooth_funct_1d_mean — ONED function op

Data kinds: signalsignal

Call: import fullseye as fs; fs.ledger.smooth_funct_1d_mean(y, size=3, iterations=1) (to call the implementation directly, import funct1d; funct1d.smooth_funct_1d_mean(y, size=3, iterations=1); from the registry, ops1d.get("smooth_funct_1d_mean"))

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`.

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.

• The canonical algorithm (author, year) and its uses are named in the family usage guide above.

Runnable examples (verified samples that actually call this op)

poc_weld_bead_profilepy -3.11 examples/poc_weld_bead_profile.py

signal_funct1dpy -3.11 examples/signal_funct1d.py

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

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

Same category (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. 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.