population op• データ種: table → table
• 呼び出し: import fullseye as fs; fs.ledger.graph_core_persistence(adjs, mode='in', weighted=False) (実装を直接呼ぶなら import graphinv; graphinv.graph_core_persistence(adjs, mode='in', weighted=False)、台帳から引くなら opsgraph.get("graph_core_persistence"))
Which nodes sit in the innermost core of every individual — K wirings on one node order.
`adjs is a list of K square matrices or a table {name: matrix}` on the same
node order (a node absent from an individual is a zero row and column). For each
individual the innermost core of :func:graph_kcore (same `mode / weighted`) is
taken; `appearances[v]` counts the individuals whose innermost core contains v.
Following Yadav & Singh 2026, a node is persistent if it is in the core of all K,
recurrent if in 2 .. K−1, transient if in exactly 1, and never otherwise.
Returns a dict: `k (K), n, names, membership` (K, n) bool,
`appearances (n,), persistent / recurrent / transient / never` (n,)
bool masks, `n_persistent .. n_never, kmax` (K,) the innermost index per
individual, `n_inner (K,), mode, weighted`.
Identities: `sum(n_inner) == sum(appearances)`; the four classes partition the
nodes; K identical inputs make every core node persistent and nothing recurrent or
transient; every persistent node is in every individual's innermost core.
Raises `ValueError: adjs` not a list / table; fewer than 2 individuals;
matrices of different sizes; any refusal of :func:graph_kcore.
• 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。
• poc_worm_core_persists — py -3.11 examples/poc_worm_core_persists.py
table を入力に取れる)graph_edge_consensus · tree_morphometry · tree_sholl · tree_run_length
population)graph_edge_consensus · graph_strength_growth
*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.