rank_spearman — IMGMETRICS iqa op

• Data kinds: any × any → scalar

• Call: import fullseye as fs; fs.ledger.rank_spearman(x, y) -> 'float' (to call the implementation directly, import iqatid; iqatid.rank_spearman(x, y) -> 'float'; from the registry, opsimgmetrics.get("rank_spearman"))

Usage

Spearman's rank correlation ρ = Pearson correlation between average ranks (the form that is correct even with ties; the classical formula 1 − 6Σd²/(n(n²−1)) agrees only when there are no ties). 1 for monotonically increasing, −1 for reversed. If either is constant, nan (rank variance is 0; correlation is undefined). ±inf contributes only its order (a perfect-match PSNR = inf is not dropped). Raises ValueError: length mismatch, fewer than 2, nan.

Detailed usage guide

• image_difference_metrics family guide

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)

• poc_iqa_fsim_gmsd_vif — py -3.11 examples/poc_iqa_fsim_gmsd_vif.py

• poc_iqa_tid2013 — py -3.11 examples/poc_iqa_tid2013.py

Ops the type connects to (they accept scalar as input)

luma_limited_u8 · rank_data · tid2013_index

Same category (iqa)

luma_limited_u8 · rank_data · rank_kendall_b · tid2013_published · tid2013_root · tid2013_index · tid2013_metric_values · tid2013_evaluate

*Provenance: iqatid.py — IMGMETRICS 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.