Nothing
# Selects an optimal graph, which is recoded to the (-1, 1) parameterization and made positive definite.
optimalGraph <- function(object, cost){
stopifnot(is(object, "elasticIsing"))
if (missing(cost)){
cost <- dimnames(object$costs)[[3]][1]
}
# Find optimals:
opt <- which(object$costs[,,cost] == min(object$costs[,,cost]), arr.ind = TRUE)
# Warning for multiple optimums:
if (nrow(opt)>1){
warning("Multiple optimums found, returning a list!")
}
cat("Optimal graph(s) found at:\n")
print(data.frame(lambda = object$lambdaMatrix[opt[,1],opt[,2]], alpha = object$alpha[opt[,2]]))
Res <- list()
for (i in seq_len(nrow(opt))){
Res[[i]] <- elasticIsingInner(object$data, object$lambdaMatrix[opt[i,1],opt[i,2]], object$alpha[opt[i,2]], and = object$and)
Res[[i]]$thresholds <- Res[[i]]$thresholds[[1]]
Res[[i]]$graph <- Res[[i]]$networks[[1]]
Res[[i]] <- Res[[i]][names(Res[[i]])!="networks"]
}
# Rescale all graphs:
Res <- lapply(Res, positiveGraph)
if (length(Res)==1){
Res <- Res[[1]]
}
return(Res)
}
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