stats op• Data kinds: conn_graph → measurement
• Call: import fullseye as fs; fs.ledger.graph_clustering_coefficient(W: 'Any') -> 'float' (to call the implementation directly, import conngraph; conngraph.graph_clustering_coefficient(W: 'Any') -> 'float'; from the registry, opsconngraph.get("graph_clustering_coefficient"))
Mean local clustering coefficient (binary graph with directions collapsed, Watts–Strogatz). Nodes with degree < 2 count as 0.
C_i = (A³)_ii / (k_i (k_i − 1)), where A is symmetric binary. 1 for a complete graph, 0 for a tree.
• 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.
• (none yet)
measurement as input)—
stats)graph_degree_table · graph_betweenness · graph_laplacian_spectrum · graph_spectral_radius · graph_components · graph_modularity · graph_rich_club · graph_motif_count
*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.