null op• データ種: matrix → table
• 呼び出し: import fullseye as fs; fs.ledger.graph_degree_preserving_null(adj, n_samples=20, swaps_per_edge=5, seed=0) (実装を直接呼ぶなら import graphinv; graphinv.graph_degree_preserving_null(adj, n_samples=20, swaps_per_edge=5, seed=0)、台帳から引くなら opsgraph.get("graph_degree_preserving_null"))
次数保存のヌルモデルで 3 サイクルと相互辺を比・z にする(各標本で次数列を厳密に保存)。
> 以下の詳細説明は原文のままです —— 要約と見出しは訳出済み。
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).
• サンプルデータ カタログ(DL URL / ライセンス) — 2-D は skimage.data(BSD/public)+ 合成、3-D は実データ源(Stanford/PDS 等)の DL URL。
• 演算子の来歴・参考文献 — この op 族の元になった研究/手法の出典。
• アルゴリズムの正典(著者・年)と用途は上記ファミリ使い方ガイドに記載。
• graphinv_three_phyla — py -3.11 examples/graphinv_three_phyla.py
table を入力に取れる)graph_edge_consensus · graph_core_persistence · tree_morphometry · tree_sholl · tree_run_length
null)—
*Provenance: graphinv.py — GRAPH operator registry. この per-op ノートは tools/opdocs.py md が自動生成(手編集しない)。*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.