graph_layout_spectral — CONNGRAPH view op

• Data kinds: conn_graph → points

• Call: import fullseye as fs; fs.ledger.graph_layout_spectral(W: 'Any', dim: 'int' = 2, seed: 'int' = 0) -> 'np.ndarray' (to call the implementation directly, import conngraph; conngraph.graph_layout_spectral(W: 'Any', dim: 'int' = 2, seed: 'int' = 0) -> 'np.ndarray'; from the registry, opsconngraph.get("graph_layout_spectral"))

Usage

Spectral layout: a point cloud (n, 3) whose coordinates are the Fiedler vectors (eigenvectors 2..dim+1) of the Laplacian with directions collapsed, each axis in [0, 1].

dim is 2 or 3 (with 2, z = 0). Each connected component is laid out first and then arranged on a grid -- for a disconnected graph the zero eigenspace is degenerate and the Fiedler vector does not necessarily separate the components, so components are separated explicitly (within a component 0.3 times the box, between components a spacing of 1).

Detailed usage guide

• conngraph 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)

• (none yet)

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

graph_edges_as_lines · graph_activity_spread · points_activity_video

Same category (view)

graph_edges_as_lines · graph_adjacency_image

*Provenance: conngraph.py — CONNGRAPH 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.