Creates a ggplot2 faceted visualization comparing robustness across multiple networks. Produces publication-quality figures similar to those in Nature Scientific Reports.
Usage
ggplot_robustness(
...,
networks = NULL,
measures = c("betweenness", "degree", "random"),
strategy = "sequential",
colors = NULL,
title = NULL,
n_iter = 1000,
seed = NULL,
type = "vertex",
ncol = NULL,
free_y = FALSE
)Arguments
- ...
Named arguments: network names as names, network objects as values.
- networks
Named list of networks (alternative to ...).
- measures
Attack strategies to compare. Default c("betweenness", "degree", "random").
- strategy
Character string; "sequential" (default) recalculates centrality after each removal, "static" uses initial centrality ranking throughout.
- colors
Named vector of colors for measures.
- title
Overall title. Default NULL.
- n_iter
Iterations for random. Default 1000.
- seed
Random seed. Default NULL.
- type
Removal type. Default "vertex".
- ncol
Columns in facet. Default NULL (auto).
- free_y
If TRUE, allow different y-axis scales per facet. Default FALSE.
Examples
if (requireNamespace("igraph", quietly = TRUE) &&
requireNamespace("ggplot2", quietly = TRUE)) {
g1 <- igraph::sample_pa(40, m = 2, directed = FALSE)
g2 <- igraph::sample_gnp(40, 0.15)
ggplot_robustness(
"Teaching network" = g1,
"Collaborative network" = g2,
n_iter = 20
)
}
