# Extract eigenvalues from an ordination analysis
#
# @param x an object returned by an ordination function.
#
# @return A numeric vector containing the eigenvalues.
# generic
eigenvalues <- function(x) {
UseMethod("eigenvalues")
}
eigenvalues.prcomp <- function(x) { x$sdev^2 }
eigenvalues.PCA <- function(x) { x$eig[,"eigenvalue"] }
eigenvalues.rda <- function(x) { as.numeric(x$CA$eig) }
eigenvalues.pca <- function(x) { x$eig }
eigenvalues.pcaRes <- function(x) { as.numeric(x@sDev^2) }
eigenvalues.CA <- function(x) { x$eig$eigenvalue }
eigenvalues.correspondence <- function(x) {
eig <- x$cor^2
# MASS allows to extract the last dimension which is meaningless (eigenvalue ~ 0)
# discard it if needed
eig <- eig[1:npc(x)]
return(eig)
}
eigenvalues.ca <- function(x) { x$sv^2 }
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