Enum: GraphRepresentation

How a Network’s connectivity is represented when evaluating coupling. This is a backend-independent performance contract, not a numerical one: both representations compute the same coupling, but a sparse representation sums over the existing edges (cost scales with the number of edges) while a dense representation operates on the full adjacency (cost scales with nodes-squared). A backend maps the choice onto its own primitives (edge gather / segment-sum vs matrix product). Orthogonal to whether the coupling reads delayed states — that is decided per coupling by its conduction delay — so the two dimensions together yield the four backend graph kinds: dense/sparse × instantaneous/delayed.

URI: tvbo:enum/GraphRepresentation

Permissible Values

Value	Meaning	Description
auto	None	Select by connection density: use the sparse representation when the adjacenc…
dense	None	Force the dense-adjacency representation
sparse	None	Force the edge-list (sparse) representation

Slots

Name	Description
graph_representation	Representation used to evaluate coupling over this network’s connectivity (``…

Identifier and Mapping Information

Schema Source

from schema: https://w3id.org/tvbo

LinkML Source

name: GraphRepresentation
description: 'How a Network''s connectivity is represented when evaluating coupling.
  This is a backend-independent performance contract, not a numerical one: both representations
  compute the same coupling, but a sparse representation sums over the existing edges
  (cost scales with the number of edges) while a dense representation operates on
  the full adjacency (cost scales with nodes-squared). A backend maps the choice onto
  its own primitives (edge gather / segment-sum vs matrix product). Orthogonal to
  whether the coupling reads *delayed* states — that is decided per coupling by its
  conduction delay — so the two dimensions together yield the four backend graph kinds:
  dense/sparse × instantaneous/delayed.'
from_schema: https://w3id.org/tvbo
rank: 1000
permissible_values:
  auto:
    text: auto
    description: 'Select by connection density: use the sparse representation when
      the adjacency is sparse enough that edge-wise evaluation is cheaper than the
      dense product, dense otherwise. Default. Lets the backend apply its own crossover
      without the recipe hard-coding a data structure.'
  dense:
    text: dense
    description: Force the dense-adjacency representation. Preferred for densely connected
      or small networks, where dense linear algebra's constant-factor efficiency outweighs
      its nodes-squared scaling.
  sparse:
    text: sparse
    description: Force the edge-list (sparse) representation. Preferred for large,
      sparsely connected networks (structural connectomes, power grids) where coupling
      cost then scales with the number of edges rather than nodes-squared.