zero_crossings_funct_1d — ONED `function` op

• Data kinds: signal → indices

• Call: import fullseye as fs; fs.ledger.zero_crossings_funct_1d(y) (to call the implementation directly, import funct1d; funct1d.zero_crossings_funct_1d(y); from the registry, ops1d.get("zero_crossings_funct_1d"))

Usage

Indices where the function changes sign (HALCON `zero_crossings_funct_1d`).

Returns the integer indices `i with sign(y[i]) * sign(y[i+1]) < 0` —

the sample *before* each crossing. An empty input returns an empty index

array (degenerate case, not an error).

Honest limitation: the test is a strict sign product, so a crossing that

lands exactly on a zero sample (`[-1, 0, 1]`) is *not* reported, nor is a

touch of zero without a sign change (`[1, 0, 1]`).

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

:returns: int index array (possibly empty).

: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)

• signal_funct1d — py -3.11 examples/signal_funct1d.py

Ops the type connects to (they accept `indices` as input)

peak_subbin

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 · 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).*

zero_crossings_funct_1d — ONED function op