local_min_max_funct_1d — ONED function op

• Data kinds: signal → table

• Call: import fullseye as fs; fs.ledger.local_min_max_funct_1d(y) (to call the implementation directly, import funct1d; funct1d.local_min_max_funct_1d(y); from the registry, ops1d.get("local_min_max_funct_1d"))

Usage

Indices of strict local maxima / minima (HALCON `local_min_max_funct_1d`).

`{"max": indices, "min": indices} where index i` is a maximum iff

`y[i] > y[i-1] and y[i] > y[i+1]` (mirrored for minima). Inputs shorter

than 3 samples have no interior point and return two empty arrays

(degenerate case, not an error).

Honest limitation: inequalities are strict — plateau extrema (equal

neighbouring samples at the top/bottom) are not reported, and the boundary

samples `0 and n-1` are never extrema.

:param y: 1-D function (may be empty).

:returns: dict `{"max": int array, "min": int array}`.

:raises ValueError: non-1-D / NaN / Inf input.

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_web_roll_periodicity — py -3.11 examples/poc_web_roll_periodicity.py

• signal_funct1d — py -3.11 examples/signal_funct1d.py

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

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Same category (function)

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 · 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.