pairs_to_table — REPRCONV pairs op

• Data kinds: pairs → table

• Call: import fullseye as fs; fs.ledger.pairs_to_table(pairs) (to call the implementation directly, import reprconv; reprconv.pairs_to_table(pairs); from the registry, opsreprconv.get("pairs_to_table"))

Usage

Pairs (N,2) → a summary table. One-way.

x_uniform is the test of "is column 0 equally spaced"; pairs for which it is False silently lose x when passed through pairs_to_signal (see the docstring above). The test uses the ratio of the largest to the smallest difference, with threshold 1e-9 (relative).

Args:

pairs: (N, 2).

Returns:

dict(n / x_min / x_max / y_min / y_max /

y_mean / x_uniform / x_step (only when equally spaced) /

pearson_r (when N >= 2 and neither column is constant)).

Raises:

ValueError: bad shape / non-finite.

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)

• representation_conversion — py -3.11 examples/representation_conversion.py

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

—

Same category (pairs)

pairs_to_signal · pairs_to_image2d

*Provenance: reprconv.py — REPRCONV 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.