create_funct_1d_pairs — ONED function op

Data kinds: signal × signalsignal

Call: import fullseye as fs; fs.ledger.create_funct_1d_pairs(x, y) (to call the implementation directly, import funct1d; funct1d.create_funct_1d_pairs(x, y); from the registry, ops1d.get("create_funct_1d_pairs"))

Usage

A 1-D function from arbitrary `(x, y) pairs, resampled to an equidistant grid (HALCON create_funct_1d_pairs`).

The pairs are sorted by x and linearly interpolated onto the integer

grid `floor(min(x)) .. ceil(max(x))` (step 1). Grid points outside the

convex hull of the data (only the two end points can be) hold the nearest

sample's value — `numpy.interp` end-hold, no extrapolation. Duplicate x

values keep numpy's interp behaviour (the segment between duplicates is a

step). Note the returned function's index 0 corresponds to physical

`x = floor(min(x))`, not necessarily 0.

:param x: 1-D abscissa values, at least 1 pair, finite.

:param y: 1-D ordinate values, same length as *x*, finite.

:returns: float64 array on the integer grid.

:raises ValueError: non-1-D / NaN / Inf input, empty input, or length mismatch.

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_veiling_glarepy -3.11 examples/poc_veiling_glare.py

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

create_funct_1d_array · smooth_funct_1d_gauss · smooth_funct_1d_mean · 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 · smooth_funct_1d_gauss · smooth_funct_1d_mean · 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.