tb_get_y_value_funct_1d — 2D `typed` op

• Data kinds: signal → feature

• Call: fullseye.apply(img, "tb_get_y_value_funct_1d", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])

tb_get_y_value_funct_1d: input → output

*The figure is the actual output on a synthetic 128×128 input. Left: input, right: output. Point clouds are drawn as a top-down scatter (brightness = z), 1-D series as a line plot, volumes as the maximum-intensity projection along z, videos as the middle frame, complex images as magnitude; return values that are not pictures are shown as the values themselves.*

*Knob a does not change the output (measured: identical at 0.1 / 0.5 / 0.9).*

*Knob b does not change the output (measured: identical at 0.1 / 0.5 / 0.9).*

Stages (the ops that come before → this op, left to right):

▸ tb_get_y_value_funct_1d: stages (docs site)

Usage

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*.

Typed bridge of the 1d op `get_y_value_funct_1d into the 2-D evolution registry: the same implementation, called under the op(v, a, b) convention. This op has no tunable parameter; a and b` are unused.

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.

Try it in Studio

The program below has been verified to run (same input as the figure). In Studio's help this block becomes buttons that load and run it on the spot.

img_to_signal 0.50 0.50
tb_get_y_value_funct_1d 0.50 0.50

▸ Load this pipeline · Load & run

Runnable examples (verified samples that actually call this op)

The examples below call the underlying ledger op get_y_value_funct_1d. This bridge op is the same implementation adapted to the fn(v, a, b) convention, so the behaviour carries over unchanged (only the call form differs).

• poc_veiling_glare — py -3.11 examples/poc_veiling_glare.py

• signal_funct1d — py -3.11 examples/signal_funct1d.py

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

identity · feature_to_img

Same category (`typed`)

tb_points_to_voxel · tb_estimate_point_normals · tb_iss_keypoints · tb_project_points · tb_render_point_depth · tb_statistical_outlier_removal · tb_radius_outlier_removal · tb_voxel_grid_downsample

*Provenance: ops.py — 2D operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

tb_get_y_value_funct_1d — 2D typed op