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

Sequence (n,) of the step (0-based) at which each node first "lit up", as integers. Nodes that never lit up get −1.

X is the (T, n) of reservoir_states. "Lit" = |x| ≥ the global maximum × thresh (thresh is in (0, 1]). There is 1 scale, not one per node -- stretching per node would make even the rounding dust of nodes that barely move count as "lit". An all-zero X gives −1 everywhere.

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.