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#' Get the Best Parameter Set
#'
#' Returns the N parameter sets which resulted in the maximum scores from \code{FUN}.
#'
#' @param optObj An object of class \code{bayesOpt}
#' @param N The number of parameter sets to return
#' @return A list containing the \code{FUN} inputs which resulted in the highest returned Score.
#' If N > 1, a \code{data.table} is returned. Each row is a result from \code{FUN}, with results ordered by
#' descending Score.
#' @examples
#' scoringFunction <- function(x) {
#' a <- exp(-(2-x)^2)*1.5
#' b <- exp(-(4-x)^2)*2
#' c <- exp(-(6-x)^2)*1
#' return(list(Score = a+b+c))
#' }
#'
#' bounds <- list(x = c(0,8))
#'
#' Results <- bayesOpt(
#' FUN = scoringFunction
#' , bounds = bounds
#' , initPoints = 3
#' , iters.n = 2
#' , gsPoints = 10
#' )
#' print(getBestPars(Results))
#' @export
getBestPars <- function(
optObj
, N = 1
) {
if (N > nrow(optObj$scoreSummary)) stop("N is greater than the iterations that have been run.")
if (N == 1) {
return(as.list(head(optObj$scoreSummary[order(-get("Score"))],1))[names(optObj$bounds)])
} else {
head(optObj$scoreSummary[order(-get("Score"))],N)[,names(optObj$bounds),with=FALSE]
}
}
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