NumSilToClusterSil {parallelpam}

NumSilToClusterSil

Description

Takes a silhouette in the form of a NumericVector, as returned by CalculateSilhouette, and returns it as a numeric matrix appropriate to be plotted by the package 'cluster'

Usage

NumSilToClusterSil(cl, s)

Arguments

cl

The array of classification with the number of the class to which each point belongs to. This number must be in 1..number_of_classes.
This function takes something like the L$clasif array which is the second element of the list returned by ApplyPAM

s

The numeric value of the silhouette for each point, with points in the same order as they appear in cl.
This is the vector returned by a call to CalculateSilhouette with the same value of parameter cl.

Value

sp A silhouette in the format of the cluster package which is a NumericMatrix with as many rows as points and three columns: cluster, neighbor and sil_width.
Its structure and dimension names are as in package 'cluster', which allows to use it with the silhouette plotting functions of such package
This means you can do library(cluster) followed by plot(NumSilToClusterSil(cl,s)) to get a beatiful plot.

Examples

# Synthetic problem: 10 random seeds with coordinates in [0..20]
# to which random values in [-0.1..0.1] are added
M<-matrix(0,100,500)
rownames(M)<-paste0("rn",c(1:100))
for (i in (1:10))
{
 p<-20*runif(500)
 Rf <- matrix(0.2*(runif(5000)-0.5),nrow=10)
 for (k in (1:10))
 {
  M[10*(i-1)+k,]=p+Rf[k,]
 }
}
tmpfile1=paste0(tempdir(),"/pamtest.bin")
JWriteBin(M,tmpfile1,dtype="float",dmtype="full")
tmpdisfile1=paste0(tempdir(),"/pamDL2.bin")
CalcAndWriteDissimilarityMatrix(tmpfile1,tmpdisfile1,distype="L2",restype="float",nthreads=0)
L <- ApplyPAM(tmpdisfile1,10,init_method="BUILD")
sil <- CalculateSilhouette(L$clasif,tmpdisfile1)
sp <- NumSilToClusterSil(L$clasif,sil)
library(cluster)
plot(sp)