function op• Data kinds: signal → measurement
• Call: import fullseye as fs; fs.ledger.get_y_value_funct_1d(y, x, interpolate=True) (to call the implementation directly, import funct1d; funct1d.get_y_value_funct_1d(y, x, interpolate=True); from the registry, ops1d.get("get_y_value_funct_1d"))
The y-value at (fractional) position *x* (HALCON `get_y_value_funct_1d`).
With `interpolate=True` (default) the value is linearly interpolated
between the two neighbouring samples; with `interpolate=False` the nearest
sample is returned.
Domain policy (documented, not extrapolated): *x* outside `[0, n-1]`
clamps to the boundary value (`numpy.interp` end-hold semantics /
index clip). HALCON's `'zero'`-border variant is not offered.
:param y: 1-D function, at least 1 sample.
:param x: finite scalar position in index units.
:param interpolate: linear interpolation (True) or nearest sample (False).
:returns: float.
:raises ValueError: non-1-D / NaN / Inf input, empty input, or non-finite *x*.
• 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.
• poc_veiling_glare — py -3.11 examples/poc_veiling_glare.py
• signal_funct1d — py -3.11 examples/signal_funct1d.py
measurement as input)—
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 · local_min_max_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.