debug <- 3
######################################################################
## Gaussian
######################################################################
bcb:::load_example(eg = "gnet", network = "asia")
## compute_scores()
scores <- bcb:::compute_scores(data = data, settings = settings,
interventions = interventions,
output = TRUE, debug = debug)
## compute_ps()
ps <- bcb:::compute_ps(settings = settings,
interventions = interventions, debug = debug)
## compute_arp()
arp <- bcb:::compute_arp(settings = settings,
interventions = interventions, debug = debug)
## ps2es()
bma <- bcb:::ps2es(ps = ps, settings = settings)
## es2mpg()
mpg <- bcb:::es2mpg(es = bma)
## convert_ps()
testthat::expect_identical(
ps,
## list -> data.frame -> list
bcb:::convert_ps(bcb:::convert_ps(ps, "data.frame"), "list")
)
## lookup(), lookup_scores(), lookup_scores_cpp()
lu <- all(unlist(lapply(settings$nodes, function(node){
apply(ps[[node]], 1, function(row){
parents <- row[seq_len(settings$max_parents)]
row[settings$max_parents + 1] ==
c(
ps[[node]][bcb:::lookup(parents = parents[!is.na(parents)],
ps_i = ps[[node]]), settings$max_parents + 1],
bcb:::lookup_score(target = node,
parents = parents,
ps = ps),
bcb:::lookup_score_cpp(parents = parents[!is.na(parents)],
ps_i = ps[[node]]),
bcb:::lookup_score_cpp(parents = parents[!is.na(parents)],
ps_i = ps[[node]],
score_col = match("score",
names(ps[[node]]))-1)
)
})
})))
testthat::expect_true(lu)
## execute_mds()
graph <- bcb:::execute_mds(ps = ps, settings = settings,
seed = 1, debug = debug)
testthat::expect_identical(dim(graph), dim(bnlearn::amat(bn.fit)))
######################################################################
## General
######################################################################
## test bida github examples
bcb:::test_bida(debug = debug)
## test mds github examples
bcb:::test_mds(debug = debug)
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