null op• 데이터 종류: matrix → table
• 호출: import fullseye as fs; fs.ledger.graph_degree_preserving_null(adj, n_samples=20, swaps_per_edge=5, seed=0)(구현을 직접 호출하려면 import graphinv; graphinv.graph_degree_preserving_null(adj, n_samples=20, swaps_per_edge=5, seed=0), 원장에서 가져오려면 opsgraph.get("graph_degree_preserving_null"))
> 이 연산자의 설명은 아직 번역이 없습니다. 원문을 그대로 싣습니다.
Compare 3-cycles and reciprocity against a degree-preserving null model.
Each null sample requests swaps_per_edge * |E| edge swaps that keep every node's in- and out-degree exactly (Maslov & Sneppen 2002); a swap that would create a self-loop or duplicate edge is skipped, so dense graphs accept fewer (swaps_accepted). The sample's degree sequences are checked against the original before it is used — a null that drifted would make every ratio a lie, so this fails closed.
Returns a dict with the observed cycles3 and reciprocal_pairs, the null *_null_mean / *_null_sd, the *_ratio (observed / null mean) and *_z, plus n_samples, swaps (requested per sample) and swaps_accepted (list, accepted per sample). Ratios are what let graphs of different size be compared; raw counts cannot.
Raises ValueError: as graph_degree_summary; n_samples < 2 (no spread to estimate); swaps_per_edge < 1; a graph with fewer than 2 edges (nothing to swap).
• 샘플 데이터 카탈로그(DL URL / 라이선스) —— 2-D 는 skimage.data(BSD/public)+ 합성, 3-D 는 실데이터 소스(Stanford/PDS 등)의 DL URL.
• 연산자의 내력·참고문헌 —— 이 연산자 족의 바탕이 된 연구/기법의 출처.
• 알고리즘의 정전(저자·연도)과 용도는 위의 패밀리 사용 가이드에 적혀 있습니다.
• graphinv_three_phyla — py -3.11 examples/graphinv_three_phyla.py
table 를 입력으로 받는 것)graph_edge_consensus · graph_core_persistence · tree_morphometry · tree_sholl · tree_run_length
null)—
*Provenance: graphinv.py — GRAPH 연산자 레지스트리. 이 op 노트는 tools/opdocs.py md 가 자동 생성합니다(직접 편집하지 마세요).*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.