sinkhorn_distance — COLORTRANSPORT `transport` op

• Data kinds: signal × signal × matrix → scalar

• Call: import colortransport; colortransport.sinkhorn_distance(a, b, cost, reg=0.05, **kw) (or opscolortransport.get("sinkhorn_distance"))

Usage

The regularised transport cost `<plan, cost>`. Not a true distance.

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

正則化のぶん系統的に偏るので、自分自身との「距離」も 0 にならない

(そのずれ幅はテストに実測で残してある)。1 次元で厳密が要るときは

:func:wasserstein_1d。

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 `scalar` as input)

—

Same category (`transport`)

wasserstein_1d · transport_plan_1d · sinkhorn · sinkhorn_divergence

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

sinkhorn_distance — COLORTRANSPORT transport op