points_to_position — REPRCONV `keypoint` op

• Data kinds: points → position

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

Usage

A point set (N,3) → its centroid (z, y, x). Not invertible (the distribution is thrown away).

The amount discarded can be measured: the RMS distance around the centroid is exactly "the spread lost by collapsing to 1 point", and selftest reports it numerically. Only when N = 1 is the round trip with position_to_points bit-identical.

Args:

points: (N, 3) (z, y, x).

Returns:

a 3-tuple of float (z, y, x).

Raises:

ValueError: invalid 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

• representation_roundtrip — py -3.11 examples/representation_roundtrip.py

Ops the type connects to (they accept `position` as input)

position_to_points

Same category (`keypoint`)

keypoints_uv_to_points · points_zyx_to_keypoints_uv · keypoints_to_image2d · keypoints_from_image2d · position_to_points

*Provenance: reprconv.py — REPRCONV operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

points_to_position — REPRCONV keypoint op