check_adjacency: Validate a spatial adjacency matrix

In tulpa: Templated Unified Library for Posterior Approximation in Bayesian Hierarchical Models

Validate a spatial adjacency matrix

Description

Check that a hand-built adjacency matrix is a well-formed spatial graph before passing it to spatial() / spatial_car(): square, finite, symmetric, zero on the diagonal, 0/1 valued, free of negative weights and of isolated nodes, and connected. adjacency() runs the same checks on the graphs it constructs. The spatial constructors refuse a graph with a missing, non-finite or negative entry.

Usage

check_adjacency(adjacency, ids = NULL)

## S3 method for class 'tulpa_adjacency_check'
print(x, ...)

Arguments

adjacency	A matrix (dense or sparse Matrix).
ids	Optional cell identifiers; if supplied, their length must match nrow(adjacency) and they must be unique.
x	A tulpa_adjacency_check report.
...	Ignored.

Value

Invisibly, a tulpa_adjacency_check list with the per-check results (square, finite, symmetric, zero_diag, binary, nonneg, isolated-node indices, n_components and component_sizes, edge count) and an overall ok flag. Issues are reported via warning() and printed; the function does not stop, so every problem surfaces in one pass.

See Also

adjacency() to construct a graph, node_index().

Examples

adj <- matrix(0, 4, 4)
for (i in 1:3) adj[i, i + 1] <- adj[i + 1, i] <- 1
check_adjacency(adj)

tulpa documentation built on Oct. 19, 2026, 5:09 p.m.