tree_run_length — GRAPH tree op

• データ種: table × signal → table

• 呼び出し: import fullseye as fs; fs.ledger.tree_run_length(tree, labels, background=0, zero_labels=None) (実装を直接呼ぶなら import treemorph; treemorph.tree_run_length(tree, labels, background=0, zero_labels=None)、台帳から引くなら opsgraph.get("tree_run_length"))

使い方

走行長(ERL): 正解の骨格を候補のラベルで塗ったとき、同じ物体のまま走れるケーブルの期待値。走行ごとの長さ、切れ目と背景で失ったケーブル、融合した走行(0 とみなす)の数。

> 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。

`labels` gives, for every node of the tree table, the candidate object it falls in.

A run is a maximal connected piece of the tree whose nodes all carry the same

label and that holds at least one edge; its length is the cable inside it (an edge

belongs to a run only if both ends share the label; a lone node between two cuts is

no run). Edges touching `background` belong to no run. Runs whose label is

in `zero_labels` (objects that also cover another skeleton — a merge) count as length

0, as in Januszewski et al. 2018: a merged run is not trustworthy anywhere.

`erl = sum(l_i^2) / L with L` the whole cable — the run length a point drawn

uniformly along the skeleton finds itself in (points on cut or background edges find

length 0). Also returns `run_lengths` (one per run, merged runs already zeroed),

`runs, max_run, cable_length, cut_edges` (both ends labelled, differently),

`background_edges and merged_runs`.

Identities: `erl == L` when every node carries one non-background label;

`sum(run_lengths) + cut cable + background cable == L`; for any labelling with

`k runs and no lost cable, erl >= L / k (Cauchy-Schwarz) and erl <= max_run`;

a path of length `L cut at m equally spaced points gives exactly L / (m + 1)`;

cut at `m uniformly random points, E[erl] = 2L / (m + 2)` (Dirichlet(1, .., 1)).

Raises `ValueError: not a tree table; labels` not one integer per node,

non-finite or non-integer.

参考(サンプルデータ・文献)

• 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。

実行できる例(この op を実際に呼ぶ検証済みサンプル)

• poc_skeleton_run_length_vs_voi — py -3.11 examples/poc_skeleton_run_length_vs_voi.py

型が繋がる次の op(table を入力に取れる)

graph_edge_consensus · graph_core_persistence · tree_morphometry · tree_sholl

同カテゴリ(tree)

tree_from_swc · tree_morphometry · tree_sholl


*Provenance: treemorph.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.