R Under development (unstable) (2024-02-11 r85891 ucrt) -- "Unsuffered Consequences"
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> # Tests for optimal intervention targets.
> 
> library(pcalg)
> 
> # Test graph: essential graph of Figure 4 in [1]. It has an unoriented component
> # with 3 vertices (1, 2, 3) and one with 2 vertices (4, 5).
> #
> # [1] A. Hauser, P. Bühlmann: Two optimal strategies for active learning of
> # causal models from interventions. Proceedings of the 6th European Workshop on
> # Probabilistic Graphical Models (PGM-2012), pp. 123 to 130, 2012.
> essgraph <- new("EssGraph",
+                 nodes = as.character(1:5),
+                 in.edges = list(2, c(1, 3), 2, c(2, 3, 5), c(2, 3, 4)),
+                 targets = list(integer(0), 1:3))
> 
> # Optimal single vertex intervention: vertex 2 (==> all edges between nodes 1,
> # 2, 3 become orientable).
> stopifnot(opt.target(essgraph, max.size = 1, use.node.names = FALSE) == 2)
> stopifnot(opt.target(essgraph, max.size = 1) == "2")
> 
> # Optimal intervention of arbitrary size: vertices 1, 3, 4 (makes all edges
> # orientable).
> stopifnot(all.equal(opt.target(essgraph, max.size = 5, use.node.names = FALSE),
+                     c(1, 3, 4)))
> stopifnot(all.equal(opt.target(essgraph), c("1", "3", "4")))
> 
> proc.time()
   user  system elapsed 
   1.28    0.21    1.48