sinkhorn — COLORTRANSPORT `transport` op

• Data kinds: signal × signal × matrix → transport_plan

• Call: import colortransport; colortransport.sinkhorn(a, b, cost, reg=0.05, n_iter=2000, tol=1e-09) (or opscolortransport.get("sinkhorn"))

Usage

The entropically regularised optimal-transport plan (Cuturi, NIPS 2013).

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

厳密解ではない。 `reg` を小さくすると厳密解に近づくが、同時に

数値的に不安定になる(指数がアンダーフローする)。`reg` を下げると

厳密解との差が縮むこと自体をテストで固定してある。

Returns

-------

ndarray

`(n, m) の輸送計画。行和・列和は a / b` に一致する

(`tol まで)。収束しなければ RuntimeError` ―― 収束しないまま

最後の反復を返すと、行和が合っていない計画が黙って下流へ流れる。

Background guides (the physics and conventions behind this op)

• colorimetry — 測色と分光の知識 — 色は「分光 × 光源 × 観測者」でしか決まらない

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.

• The canonical algorithm (author, year) and its uses are named in the family usage guide above.

Runnable examples (verified samples that actually call this op)

• color_transport — py -3.11 examples/color_transport.py

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

transport_cost · apply_transport

Same category (`transport`)

wasserstein_1d · transport_plan_1d · sinkhorn_distance · sinkhorn_divergence

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

sinkhorn — COLORTRANSPORT transport op