pairs op• Data kinds: pairs → image2d
• Call: import fullseye as fs; fs.ledger.pairs_to_image2d(pairs, shape=(64, 64)) (to call the implementation directly, import reprconv; reprconv.pairs_to_image2d(pairs, shape=(64, 64)); from the registry, opsreprconv.get("pairs_to_image2d"))
Pairs (N,2) → a scatter-density image (H, W). The third exit from pairs.
Maps column 0 to the row direction and column 1 to the column direction, normalises each by its own min-max and drops them into bins (2-D histogram). It is meant for viewing as a phase plot or correlation plot, and is irreversible (the quantization by the bin width + the normalisation discard the scale of the absolute values). So that the discarded scale can be restored, extent is... not returned -- returning it would make this no longer an image2d. If needed, use x_min etc. of pairs_to_table.
A constant column (min == max) is gathered at position 0.5 (this avoids division by 0, but so that it is not read as "the density is concentrated at the centre", only 1 bin is raised).
Args:
pairs: (N, 2).
shape: (H, W).
Returns:
(H, W) float64, density normalised to a maximum of 1.0.
Raises:
ValueError: bad shape / non-finite / shape exceeds the limit.
• 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.
• representation_conversion — py -3.11 examples/representation_conversion.py
image2d as input)pairs)pairs_to_signal · pairs_to_table
*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.