pairs_to_table — REPRCONV `pairs` op

• Data kinds: pairs → table

• Call: import reprconv; reprconv.pairs_to_table(pairs) (or opsreprconv.get("pairs_to_table"))

Usage

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

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

`x_uniform` は「列 0 が等間隔か」の判定で、これが False の対を

:func:pairs_to_signal に通すと x が黙って落ちる(上の docstring 参照)。

判定は最大差分と最小差分の比で行い、閾値は 1e-9(相対)。

Args:

pairs: (N, 2)。

Returns:

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

`y_mean / x_uniform / x_step`(等間隔のときのみ) /

`pearson_r`(N >= 2 かつ両列が定数でないとき))。

Raises:

ValueError: 形状不正 / 非有限。

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).*

pairs_to_table — REPRCONV pairs op