a3_distribution — 3D `shape_descriptor` op

• Data kinds: points → descriptor

• Call: import fullseye as fs; fs.ledger.a3_distribution(points, bins: 'int' = 64, samples: 'int' = 100000, seed: 'int' = 0) -> 'np.ndarray' (to call the implementation directly, import descriptors3d; descriptors3d.a3_distribution(points, bins: 'int' = 64, samples: 'int' = 100000, seed: 'int' = 0) -> 'np.ndarray'; from the registry, ops3d.get("a3_distribution"))

Usage

The distribution of the angle three random points (A, B, C) subtend at vertex B (Osada 2002's A3).

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

角度は回転・平行移動・スケールのすべてに不変(スケールしても角は変わらない)ため、

D2 と相補的な無次元の形状特徴になる。レンジ [0, π] 固定の正規化ヒストグラム

(bins,) を返す(総和 1)。空間的に重なった点(ゼロ長ベクトル)は角が未定義なので

除外する。

Parameters

----------

points : array_like, shape (N, 3)

点群。N >= 3 が必要。

bins, samples, seed :

d2_distribution と同義。

Returns

-------

np.ndarray, shape (bins,)

正規化角度ヒストグラム(ラジアン、[0, π])。

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)

• shape_desc_pose — py -3.11 examples_3d/shape_desc_pose.py

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

fuse_to_voxel · shape_distance

Same category (`shape_descriptor`)

d2_distribution · extent_signature · describe · shape_distance

*Provenance: descriptors3d.py — 3D operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

a3_distribution — 3D shape_descriptor op