Nothing
`Migration` <-
function(CurrentPred=NULL, FutureProj=NULL, X=NULL, Y=NULL, MaxMigr=NULL, Pred.Save=NULL)
{
#if(dim(CurrentPred)[1] != dim(FutureProj)[1])
#stop("\n\n Number of pixel should be the same in CurrentPred, FutureProj, X and Y")
#if(dim(CurrentPred)[2] != dim(FutureProj)[2])
#stop("\n\n Species number should be the same in CurrentPred and FutureProj")
CurrentPred <- as.data.frame(CurrentPred)
FutureProj <- as.data.frame(FutureProj)
PredMigr <- as.data.frame(matrix(0, nrow=nrow(CurrentPred)))
if(length(MaxMigr) == 1 | length(MaxMigr) == ncol(CurrentPred)){
if(length(MaxMigr) == 1) MaxMigr <- rep(MaxMigr, ncol(CurrentPred)) #duplicate to nb of columns extent
for(j in 1:ncol(CurrentPred)){
if(sum(FutureProj[CurrentPred[, j] == 0, j]) != 0)
PredMigr[, j] <- .Dispersal.Limit(CurrentPred[, j], FutureProj[, j], X, Y, MaxMigr[j])
else PredMigr[, j] <- FutureProj[, j]
}
} else stop("\n Incorrect values in MaxMigr, does not match the number of columns of data input")
#Saving the results; checking if object already created
if(!is.null(Pred.Save)){
if(exists(Pred.Save, where=1)) {
New.Pred.Save <- unique(Pred.Save, pos=1)
assign(New.Pred.Save, PredMigr, pos=1)
warning(paste("\n Prediction with dispersal saved in", New.Pred.Save, "\n -> object overwritten \n"))
}
else assign(Pred.Save, PredMigr, pos=1)
}
}
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