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Data X:
95.90 2.90 96.92 95.86 96.06 2.63 96.06 96.02 96.31 2.67 96.59 96.34 96.34 1.81 96.67 96.84 96.49 1.33 97.27 96.73 96.22 0.88 96.38 96.34 96.53 1.28 96.47 96.60 96.50 1.26 96.05 96.64 96.77 1.26 96.76 97.20 96.66 1.29 96.51 97.50 96.58 1.10 96.55 96.99 96.63 1.37 95.97 97.08 97.06 1.21 97.00 97.55 97.73 1.74 97.46 98.42 98.01 1.76 97.90 98.78 97.76 1.48 98.42 97.49 97.49 1.04 98.54 96.99 97.77 1.62 99.00 97.16 97.96 1.49 98.94 97.29 98.23 1.79 99.02 97.80 98.51 1.80 100.07 98.12 98.19 1.58 98.72 98.03 98.37 1.86 98.73 98.11 98.31 1.74 98.04 98.07 98.60 1.59 99.08 98.21 98.97 1.26 99.22 98.48 99.11 1.13 99.57 98.83 99.64 1.92 100.44 99.20 100.03 2.61 100.84 99.88 99.98 2.26 100.75 99.71 100.32 2.41 100.49 100.03 100.44 2.26 99.98 100.60 100.51 2.03 99.96 100.85 101.00 2.86 99.76 101.96 100.88 2.55 100.11 101.40 100.55 2.27 99.79 100.81 100.83 2.26 100.29 100.66 101.51 2.57 101.12 101.55 102.16 3.07 102.65 102.23 102.39 2.76 102.71 102.90 102.54 2.51 103.39 102.68 102.85 2.87 102.80 103.41 103.47 3.14 102.07 104.62 103.57 3.11 102.15 104.93 103.69 3.16 101.21 105.88 103.50 2.47 101.27 105.18 103.47 2.57 101.86 104.54 103.45 2.89 101.65 104.58 103.48 2.63 101.94 104.34 103.93 2.38 102.62 104.66 103.89 1.69 102.71 104.73 104.40 1.96 103.39 105.44 104.79 2.19 104.51 105.72 104.77 1.87 104.09 105.68 105.13 1.60 104.29 105.90 105.26 1.63 104.57 105.97 104.96 1.22 105.39 105.21 104.75 1.21 105.15 104.75 105.01 1.49 106.13 104.89 105.15 1.64 105.46 105.26 105.20 1.66 106.47 104.84 105.77 1.77 106.62 105.47 105.78 1.82 106.52 105.40 106.26 1.78 108.04 105.73 106.13 1.28 107.15 105.72 106.12 1.29 107.32 105.63 106.57 1.37 107.76 105.97 106.44 1.12 107.26 105.92 106.54 1.51 107.89 106.32
Names of X columns:
1 2 3 4
Method
single
ward
single
complete
average
mcquitty
median
centroid
# of (top) clusters to display
ALL
ALL
2
3
4
5
6
7
8
9
10
15
20
Horizontal
FALSE
FALSE
TRUE
Triangle
FALSE
FALSE
TRUE
Chart options
Title:
Label y-axis:
Label x-axis:
R Code
par3 <- as.logical(par3) par4 <- as.logical(par4) if (par3 == 'TRUE'){ dum = xlab xlab = ylab ylab = dum } x <- t(y) hc <- hclust(dist(x),method=par1) d <- as.dendrogram(hc) str(d) mysub <- paste('Method: ',par1) bitmap(file='test1.png') if (par4 == 'TRUE'){ plot(d,main=main,ylab=ylab,xlab=xlab,horiz=par3, nodePar=list(pch = c(1,NA), cex=0.8, lab.cex = 0.8),type='t',center=T, sub=mysub) } else { plot(d,main=main,ylab=ylab,xlab=xlab,horiz=par3, nodePar=list(pch = c(1,NA), cex=0.8, lab.cex = 0.8), sub=mysub) } dev.off() if (par2 != 'ALL'){ if (par3 == 'TRUE'){ ylab = 'cluster' } else { xlab = 'cluster' } par2 <- as.numeric(par2) memb <- cutree(hc, k = par2) cent <- NULL for(k in 1:par2){ cent <- rbind(cent, colMeans(x[memb == k, , drop = FALSE])) } hc1 <- hclust(dist(cent),method=par1, members = table(memb)) de <- as.dendrogram(hc1) bitmap(file='test2.png') if (par4 == 'TRUE'){ plot(de,main=main,ylab=ylab,xlab=xlab,horiz=par3, nodePar=list(pch = c(1,NA), cex=0.8, lab.cex = 0.8),type='t',center=T, sub=mysub) } else { plot(de,main=main,ylab=ylab,xlab=xlab,horiz=par3, nodePar=list(pch = c(1,NA), cex=0.8, lab.cex = 0.8), sub=mysub) } dev.off() str(de) } load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Summary of Dendrogram',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Label',header=TRUE) a<-table.element(a,'Height',header=TRUE) a<-table.row.end(a) num <- length(x[,1])-1 for (i in 1:num) { a<-table.row.start(a) a<-table.element(a,hc$labels[i]) a<-table.element(a,hc$height[i]) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable1.tab') if (par2 != 'ALL'){ a<-table.start() a<-table.row.start(a) a<-table.element(a,'Summary of Cut Dendrogram',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Label',header=TRUE) a<-table.element(a,'Height',header=TRUE) a<-table.row.end(a) num <- par2-1 for (i in 1:num) { a<-table.row.start(a) a<-table.element(a,i) a<-table.element(a,hc1$height[i]) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable2.tab') }
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