Build an organ-interaction network from TDS — tdsNetwork • PhysioNetPhysiology

Thresholds a TDS matrix into a weighted, undirected network: nodes are physiological systems and edges are stable dynamic couplings whose weight is the TDS percentage. Edges below threshold are removed.

Usage

tdsNetwork(
  x,
  threshold = NULL,
  surrogate = FALSE,
  X = NULL,
  n_surrogates = 50,
  quantile = 0.95
)

Arguments

x: A "tds" object from timeDelayStability(), or a symmetric numeric TDS matrix.
threshold: Minimum TDS percentage for an edge to be kept. If NULL (default) and surrogate = TRUE, a surrogate threshold is computed with tdsSurrogateThreshold(); otherwise a value must be supplied.
surrogate: Logical; if TRUE and threshold is NULL, derive the threshold from phase-randomised surrogates. Requires x to be a "tds" object (so the underlying series and windowing are available) — supply the original node matrix via X.
X: Original node matrix, required when surrogate = TRUE.
n_surrogates, quantile: Passed to tdsSurrogateThreshold().

Value

An object of class "tds_network": a list with adjacency (weighted, thresholded), threshold, nodes, degree (number of links per node), strength (summed edge weight per node), and edges (a data frame of the surviving links).

Examples

set.seed(1)
n <- 3000
x <- as.numeric(stats::filter(rnorm(n), rep(1/5, 5), sides = 2)); x[is.na(x)] <- 0
y <- c(rep(0, 5), x[seq_len(n - 5)]) + rnorm(n, sd = 0.3)
z <- rnorm(n)
X <- cbind(brain = x, heart = y, muscle = z)
res <- timeDelayStability(X, window = 100, step = 50, max_lag = 20, min_stable = 3)
net <- tdsNetwork(res, threshold = 40)
net$edges
#>    from    to tds lag
#> 1 brain heart 100   5