tb_jitter — 2D `typed` op

• Data kinds: points → points

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

*No figure: this op takes points as input. A Studio program starting from an image cannot reach that type — see the runnable examples below for how it is used.*

Usage

Adds isotropic Gaussian noise `N(0, sigma)` to each point (mimicking sensor position noise).

> The detailed description below is the original text — the summary and the headings are translated.

`sigma はワールド単位の標準偏差(ユーザ指定パラメータ)。clip` を与えると

各成分の変位を `[-clip, clip]` に切り詰める(外れ変位の抑制)。大 N ではノイズの

平均≈0・標準偏差≈sigma となる。返り値は入力と同形状 `(N,3)`。

2-D 進化レジストリへ橋渡しした 3d の op `jitter。実装は同じで、呼び出し規約だけ op(v, a, b) に合わせてある。この op に調整点は無く、a も b` も使われない。

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.

Runnable examples (verified samples that actually call this op)

• (none yet)

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

identity · tb_points_to_voxel · tb_estimate_point_normals · tb_iss_keypoints · tb_angle_3points · tb_project_points · tb_render_point_depth · tb_statistical_outlier_removal

Same category (`typed`)

tb_points_to_voxel · tb_estimate_point_normals · tb_iss_keypoints · tb_angle_3points · tb_project_points · tb_render_point_depth · tb_statistical_outlier_removal · tb_radius_outlier_removal

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

tb_jitter — 2D typed op