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##############################################################################
# Function "DistMatrices()" computes similarity matrices for the data matrix #
# and each cluster #
# #
# Input Parameters: #
# 1) Data #
# 2) Cluster assignment vector from RunKmeans() function #
# #
# Returns to the end user: #
# 1) D_Full #
# 2) D_Subset{i} #
# #
# Date: August 12, 2005 #
# written by: Brian Steinmeyer #
##############################################################################
## calculate Euclidean distance matrix for all samples
## calculate Euclidean distance matrix for each cluster
## return to end user
DistMatrices <- function(x.data, cluster.assignment) {
tdist <- function(p) dist(t(p))
dist.full <- dist(t(x.data))
Dsub.i <- by(x.data, cluster.assignment, tdist)
return(list(Dsubsets=Dsub.i, Dfull=dist.full))
}
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