R version 2.6.0 (2007-10-03)
Copyright (C) 2007 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- array(list(1,20,5,2,60,3,2,75,4,2,75,4,1,15,3,2,40,3,1,40,4,2,50,4,2,30,4,2,30,3,2,30,3,2,20,4,2,90,3,2,25,3,1,60,3,2,30,2,2,60,3,2,150,3,1,30,4,2,40,3,2,50,3,2,20,3,2,45,4,1,45,2,1,30,4,2,30,3,3,75,4,1,60,3,3,60,3,2,120,3,2,35,4,2,70,3,2,50,3,2,25,4,2,45,3,1,20,5,2,45,4,2,45,4,2,55,4,2,45,4,2,35,3,2,60,3,1,40,3,2,45,5,2,55,3,2,40,3,2,40,3,2,20,3,1,20,3,2,50,4,2,20,3),dim=c(3,51),dimnames=list(c('difficulty','preperationtime','ranking'),1:51))
>  y <- array(NA,dim=c(3,51),dimnames=list(c('difficulty','preperationtime','ranking'),1:51))
>  for (i in 1:dim(x)[1])
+  {
+  	for (j in 1:dim(x)[2])
+  	{
+  		y[i,j] <- as.numeric(x[i,j])
+  	}
+  }
> par7 = '-0.5'
> par6 = '0'
> par5 = '0.5'
> par4 = '0.5'
> par3 = '1'
> par2 = 'single'
> par1 = 'euclidean'
> ylab = 'height'
> xlab = 'cases'
> main = 'Dendrogram'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: Wessa, P., (2007), Agglomerative Nesting (v1.0.1) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_agglomerativehierarchicalclustering.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> par3 <- as.numeric(par3)
> par4 <- as.numeric(par4)
> par5 <- as.numeric(par5)
> par6 <- as.numeric(par6)
> par7 <- as.numeric(par7)
> library(cluster)
> if (par2 == 'flexible')
+ {
+ if (par3 == 1) pm <- c(par4)
+ if (par3 == 3) pm <- c(par4,par5,par6)
+ if (par3 == 4) pm <- c(par4,par5,par6,par7)
+ ag <- agnes(t(y),metric=par1,method=par2,par.method=pm)
+ } else {
+ ag <- agnes(t(y),metric=par1,method=par2)
+ }
> mysub <- paste('Method: ',par2)
> summary(ag)
Object of class `agnes' from call:
 agnes(x = t(y), metric = par1, method = par2) 
Agglomerative coefficient:  0.9329761 
Order of objects:
 [1] 1  36 12 22 48 51 49 5  2  17 42 29 15 28 6  20 46 47 7  43 9  19 25 10 11
[26] 26 16 31 41 14 34 8  50 21 33 39 45 23 37 38 40 44 35 24 3  4  27 32 13 18
[51] 30
Merge:
      [,1] [,2]
 [1,]  -48  -51
 [2,]  -46  -47
 [3,]  -38  -40
 [4,]  -37    3
 [5,]  -23    4
 [6,]  -22    1
 [7,]  -21  -33
 [8,]  -20    2
 [9,]  -19  -25
[10,]  -17  -42
[11,]  -15  -28
[12,]  -11  -26
[13,]  -10   12
[14,]   -8  -50
[15,]   -6    8
[16,]   -3   -4
[17,]   -2   10
[18,]   -1  -36
[19,]  -39  -45
[20,]  -31  -41
[21,]    5  -44
[22,]   21  -35
[23,]    6  -49
[24,]  -14  -34
[25,]  -12   23
[26,]   13  -16
[27,]   -9    9
[28,]   27   26
[29,]   14    7
[30,]   -7  -43
[31,]   15   30
[32,]   16  -27
[33,]   17  -29
[34,]   33   11
[35,]   22  -24
[36,]   18   25
[37,]   28   20
[38,]   37   24
[39,]   29   19
[40,]   39   35
[41,]   31   38
[42,]   41   40
[43,]   34   42
[44,]   36   -5
[45,]   44   43
[46,]   32  -32
[47,]   45   46
[48,]   47  -13
[49,]  -18  -30
[50,]   48   49
Height:
 [1]  0.000000  1.414214  1.000000  0.000000  0.000000  1.000000  5.000000
 [8]  5.000000  0.000000  0.000000  1.000000  1.000000  0.000000  5.000000
[15]  0.000000  0.000000  0.000000  1.000000  1.000000  5.000000  1.000000
[22]  0.000000  1.000000  0.000000  0.000000  1.000000  5.000000  1.000000
[29]  5.000000  1.000000  5.000000  0.000000  1.000000  0.000000  5.000000
[36]  1.000000  5.000000  0.000000  0.000000  0.000000  1.000000  1.000000
[43]  1.414214 10.000000  0.000000  1.000000  5.099020 15.033296 30.000000
[50] 30.000000

1275 dissimilarities, summarized :
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
  0.000  10.050  20.000  25.568  30.058 135.000 
Metric :  euclidean 
Number of objects : 51

Available components:
[1] "order"     "height"    "ac"        "merge"     "diss"      "call"     
[7] "method"    "order.lab" "data"     
> postscript(file="/var/www/html/rcomp/tmp/1whf81196051059.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(ag,which.plots=2,main=main,sub=mysub,xlab=xlab,ylab=ylab)
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/2nnkw1196051059.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(ag,which.plots=1,main='Banner',sub=mysub,xlab=ylab,ylab=xlab)
> dev.off()
null device 
          1 
> load(file='/var/www/html/rcomp/createtable')
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Agglomerative Nesting (Hierarchical Clustering)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Agglomerative Coefficient',header=TRUE)
> a<-table.element(a,ag$ac)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/3xc0d1196051059.tab") 
> 
> system("convert tmp/1whf81196051059.ps tmp/1whf81196051059.png")
> system("convert tmp/2nnkw1196051059.ps tmp/2nnkw1196051059.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.811   0.312   1.115