##' Complete copy of nlpca net object
##' @param nlnet a nlnet
##' @return A copy of the input nlnet
##' @author Henning Redestig
forkNlpcaNet <- function(nlnet) {
res <- new("nlpcaNet")
res@net <- nlnet@net
res@hierarchic <- nlnet@hierarchic
res@fct <- nlnet@fct
res@fkt <- nlnet@fkt
res@weightDecay <- nlnet@weightDecay
res@featureSorting <- nlnet@featureSorting
res@dataDist <- nlnet@dataDist
res@inverse <- nlnet@inverse
res@fCount <- nlnet@fCount
res@componentLayer <- nlnet@componentLayer
res@error <- nlnet@error
res@gradient <- nlnet@gradient
res@weights <- weightsAccount(nlnet@weights$current())
res@maxIter <- nlnet@maxIter
res@scalingFactor <- nlnet@scalingFactor
res
}
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