sinkhorn_distance — COLORTRANSPORT transport op

• Data kinds: signal × signal × matrix → scalar

• Call: import fullseye as fs; fs.ledger.sinkhorn_distance(a, b, cost, reg=0.05, **kw) (to call the implementation directly, import colortransport; colortransport.sinkhorn_distance(a, b, cost, reg=0.05, **kw); from the registry, opscolortransport.get("sinkhorn_distance"))

Usage

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

Because of the regularisation it is systematically biased, so even the "distance" to itself is not 0 (the size of that offset is kept in the tests as a measured value). When exactness is needed in 1 dimension, wasserstein_1d.

Background guides (the physics and conventions behind this op)

• colorimetry — Colorimetry and spectra — colour is fixed only by spectrum × illuminant × observer

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)

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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).*

© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.