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#' Filters for size
#'
#' Filters out the Subcascades object for the given sizes.
#'
#' @inheritParams subcascades
#' @inheritParams summarySubcascades
#'
#' @param size
#' A numeric value that defines the size of the cascades that should be returned.
#' The smallest size is 2 and the largest the maximal number of classes of the current dataset.
#'
#' @return
#' A Subcascades object as in \code{\link{subcascades}}, that does not include cascades of the specific lengths that hve been filtered.
#'
#' @seealso \code{\link{keepSize}}, \code{\link{dropSets}}, \code{\link{keepSets}}, \code{\link{dropThreshold}}, \code{\link{keepThreshold}}
#'
#' @examples
#' library(TunePareto)
#' data(esl)
#' data = esl$data
#' labels = esl$labels
#' foldList = generateCVRuns(labels = labels,
#' ntimes = 2,
#' nfold = 2,
#' leaveOneOut = FALSE,
#' stratified = TRUE)
#' predMap = predictionMap(data, labels, foldList = foldList,
#' classifier = tunePareto.svm(), kernel='linear')
#' # generate Subcascades object
#' subc = subcascades(predMap,thresh=0.7)
#'
#' # filters out cascades that have a length of 3
#' dropSize(subc,size=3)
#' # filters out cascades that have a length of 3 or 4
#' dropSize(subc, size=c(3,4))
dropSize <- function(subcascades=NULL, size = NA)
{
#################################################
##
## Check parameter 'subcascades'
if(is.null(subcascades))
return(NULL)
if(!inherits(subcascades, 'Subcascades'))
stop(errorStrings('subcascades'))
#################################################
##
## Check parameter 'size'
if(all(is.na(size)))
return(subcascades)
if(!is.numeric(size)|any(is.na(size)))
stop(errorStrings('size.na'))
#################################################
subcascades <- subcascades[sapply(subcascades, function(x){!is.null(x)})]
if(length(subcascades)==0)
return(NULL)
size <- paste('size.',unique(size), sep = '')
keep <- !(names(subcascades) %in% size)
if(sum(keep)==0)
return(NULL)
subcascades <- subcascades[keep]
class(subcascades) <- 'Subcascades'
return(subcascades)
}
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