R Under development (unstable) (2024-09-06 r87103 ucrt) -- "Unsuffered Consequences"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> # 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 
   0.79    0.12    0.92