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##
## hypervolume.r - Functions for calculating the dominated hypervolume
##
## Authors:
## Olaf Mersmann <olafm@statistik.uni-dortmund.de>
##
##' Dominated Hypervolume calculation
##'
##' \code{dominated_hypervolume} calculates the dominated hypervolume of
##' the points in \code{points}.
##'
##' \code{hypervolume_contribution} calculates the hypervolume
##' contribution of each point.
##'
##' If no reference point \code{ref} is given, one is automatically
##' calculated by determening the maximum in each coordinate.
##'
##' Currently only one general algorithm is implemented due to Fonseca
##' et.al. but work is underway to include others such as the Beume &
##' Rudolph approach as well as the approach by Bradstreet et.al.
##'
##' The 1D and 2D cases are handle seperately by efficient algorithms.
##' Calculates the exact dominated hypervolume of the points given in
##' \code{x} subject to the reference point \code{ref}.
##'
##' @param points Matrix containing the points one per column.
##' @param ref Optional reference point. If not provided the maximum
##' in each dimension is used.
##' @return For \code{dominated_hypervolume} the dominated hypervolume
##' by the points in \code{points} with respect to the reference point
##' \code{ref}. For \code{hypervolume_contribution} a vector giving
##' the hypervolume soley dominated by that point.
##'
##' @seealso \code{\link{nondominated_points}} to extract the pareto
##' front approximation from a given set of points and
##' \code{\link{nds_hv_selection}} for a selection strategy based on
##' the hypervolume contribution of each point.
##'
##' @references
##' This code uses version 1.3 of the hypervolume code available from
##' \url{ https://lopez-ibanez.eu/hypervolume}. For a
##' description of the algorithm see
##'
##' Carlos M. Fonseca, Luis Paquete, and Manuel Lopez-Ibanez. \emph{An
##' improved dimension-sweep algorithm for the hypervolume
##' indicator}. In IEEE Congress on Evolutionary Computation, pages
##' 1157-1163, Vancouver, Canada, July 2006.
##'
##' @author Olaf Mersmann \email{olafm@@statistik.tu-dortmund.de}
##'
##' @export
##' @keywords optimize
dominated_hypervolume <- function(points, ref) {
## Possibly infer reference point:
if (missing(ref))
ref <- apply(points, 1, max)
## Sanity checks:
if (!is.matrix(points))
stop("Pareto front must be a matrix")
if (nrow(points) != length(ref))
stop("Reference point and front must have the same dimension.")
if (!all(is.finite(ref))) {
warning("Reference point containes non finite values.")
return(NaN)
}
if (!all(is.finite(points))) {
warning("Front includes non finite points.")
return(NaN)
}
.Call(do_dominated_hypervolume, points, ref, PACKAGE="emoa")
}
##' @export
##' @rdname dominated_hypervolume
hypervolume_contribution <- function(points, ref) {
## Possibly infer reference point:
if (missing(ref))
ref <- apply(points, 1, max) + 1
## Sanity checks:
if (!is.matrix(points))
stop("Pareto front must be a matrix")
if (nrow(points) != length(ref))
stop("Reference point and front must have the same dimension.")
## Call C code:
.Call(do_hv_contrib, points, ref, PACKAGE="emoa")
}
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