graph_activation_latency — CONNGRAPH activity op

• Data kinds: matrix → labels

• Call: import fullseye as fs; fs.ledger.graph_activation_latency(X: 'Any', thresh: 'float' = 0.1) -> 'np.ndarray' (to call the implementation directly, import conngraph; conngraph.graph_activation_latency(X: 'Any', thresh: 'float' = 0.1) -> 'np.ndarray'; from the registry, opsconngraph.get("graph_activation_latency"))

Usage

> This operator's description has not been translated yet. The original text follows as it is.

各ノードが初めて「点いた」ステップ(0 始まり)の列 (n,)、整数。点かなかったノードは −1。

`X` は reservoir_states の (T, n)。「点いた」= |x| ≥ 全体の最大値 × thresh(thresh は

(0, 1])。尺度はノードごとでなく 1 つ —— ノードごとに伸ばすと、ほとんど動かないノードの

丸め屑も「点いた」になる。全零の X はすべて −1。

Detailed usage guide

• conngraph family guide

References (sample data, literature)

• 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.

Runnable examples (verified samples that actually call this op)

• poc_malecns_activity_wave — py -3.11 examples/poc_malecns_activity_wave.py

Ops the type connects to (they accept labels as input)

graph_modularity · graph_activity_spread · graph_block_shuffle · graph_layer_propagate · states_layer_dimension

Same category (activity)

graph_activity_spread · points_activity_video

*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.