tb_estimate_alpha — 2D `typed` op

• Data kinds: points → feature

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

tb_estimate_alpha: 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_estimate_alpha: stages (docs site)

Usage

Returns a recommended alpha based on the scale of the point cloud (based on the median nearest-neighbor distance).

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

各点の最近傍距離の中央値 `m` を求め、半径しきい値 1/alpha ≈ 2m(隣接間隔の約 2 倍まで

許す)となるよう `alpha = 1/(2m)` を返す。これで表面付近の素性の良い四面体は残しつつ、

大きく間延びした四面体(=凹み・外側)を切り落とせる。重複点は最近傍 0 になるため正の距離のみ使う。

Parameters

----------

points : array_like (N,3)

Returns

-------

alpha : float

正の有限値。

2-D 進化レジストリへ橋渡しした 3d の op `estimate_alpha。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.

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_points 0.50 0.50
tb_estimate_alpha 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 estimate_alpha. 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).

• alpha_shape_topology — py -3.11 examples_3d/alpha_shape_topology.py

• sfm_recon — py -3.11 examples_3d/sfm_recon.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_estimate_alpha — 2D typed op