# This function is part of hte depeche function
# Here, a cluster center matrix is created that relates its values to the
# original indata variables, which increases the interpretability vastly.
# "Unique" flags:
# reducedClusterCenters: the selected cluster centers, where only variables
# that have not been completely sparsed out are kept.
depecheGroundCenters <- function(reducedClusterCenters, logCenterSd){
# First, the cluster centers are multiplied by the standard deviation of
# the data
clusterCentersMultSd <- reducedClusterCenters * logCenterSd[[3]]
# Then, the center term is added to all
# variables separately
if (is.logical(logCenterSd[[2]]) == FALSE) {
groundClusterCenters <-
do.call("cbind",lapply(seq_len(ncol(clusterCentersMultSd)),
function(i){
clusterCentersMultSd[, i] + logCenterSd[[2]][i]
}))
groundClusterCenters[which(reducedClusterCenters == 0)] <- 0
} else {
groundClusterCenters <- clusterCentersMultSd
}
dimnames(groundClusterCenters) <- dimnames(reducedClusterCenters)
groundClusterCenters
}
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