R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> x <- array(list(3010
+ ,2590
+ ,11290
+ ,4700
+ ,44.51
+ ,2910
+ ,2080
+ ,11620
+ ,4960
+ ,45.48
+ ,3840
+ ,2640
+ ,10790
+ ,4880
+ ,53.1
+ ,3580
+ ,3000
+ ,8380
+ ,4090
+ ,51.88
+ ,3140
+ ,2350
+ ,9370
+ ,3450
+ ,48.65
+ ,3550
+ ,2220
+ ,10090
+ ,3020
+ ,54.35
+ ,3250
+ ,2540
+ ,11130
+ ,3070
+ ,57.52
+ ,2820
+ ,2700
+ ,10530
+ ,3720
+ ,63.98
+ ,2260
+ ,2580
+ ,10490
+ ,3750
+ ,62.91
+ ,2060
+ ,2420
+ ,10570
+ ,3910
+ ,58.54
+ ,2120
+ ,2090
+ ,11170
+ ,4120
+ ,55.24
+ ,2210
+ ,2000
+ ,11610
+ ,4780
+ ,56.86
+ ,2190
+ ,1860
+ ,10920
+ ,3070
+ ,62.99
+ ,2180
+ ,1980
+ ,11570
+ ,4100
+ ,60.21
+ ,2350
+ ,2690
+ ,12960
+ ,3900
+ ,62.06
+ ,2440
+ ,3040
+ ,11190
+ ,3020
+ ,70.26
+ ,2370
+ ,2450
+ ,11920
+ ,3220
+ ,69.78
+ ,2440
+ ,2650
+ ,14930
+ ,4030
+ ,68.56
+ ,2610
+ ,2710
+ ,14520
+ ,4210
+ ,73.67
+ ,3040
+ ,3230
+ ,12970
+ ,4510
+ ,73.23
+ ,3190
+ ,3160
+ ,13870
+ ,4320
+ ,61.96
+ ,3120
+ ,3040
+ ,13250
+ ,3890
+ ,57.81
+ ,3170
+ ,2630
+ ,12760
+ ,7280
+ ,58.76
+ ,3600
+ ,2730
+ ,14050
+ ,9640
+ ,62.47
+ ,3420
+ ,2830
+ ,14660
+ ,5680
+ ,53.68
+ ,3650
+ ,2320
+ ,15010
+ ,6320
+ ,57.56
+ ,4180
+ ,2410
+ ,15020
+ ,5820
+ ,62.05
+ ,2960
+ ,3080
+ ,13090
+ ,4890
+ ,67.49
+ ,2710
+ ,2260
+ ,13190
+ ,3320
+ ,67.21
+ ,2950
+ ,2300
+ ,11390
+ ,2930
+ ,71.05
+ ,3030
+ ,3600
+ ,10110
+ ,3530
+ ,76.93
+ ,3770
+ ,3380
+ ,8240
+ ,3690
+ ,70.76
+ ,4740
+ ,3670
+ ,7920
+ ,3750
+ ,77.17
+ ,4450
+ ,3040
+ ,7700
+ ,3330
+ ,82.34
+ ,5550
+ ,2840
+ ,7920
+ ,4790
+ ,92.41
+ ,5580
+ ,2810
+ ,8130
+ ,5990
+ ,90.93
+ ,5890
+ ,2980
+ ,10510
+ ,5290
+ ,92.18
+ ,7480
+ ,2440
+ ,10230
+ ,5310
+ ,94.99
+ ,10450
+ ,2620
+ ,10940
+ ,4790
+ ,103.64
+ ,6360
+ ,2270
+ ,9230
+ ,3630
+ ,109.07
+ ,6710
+ ,2540
+ ,10320
+ ,2820
+ ,122.8
+ ,6200
+ ,3060
+ ,9590
+ ,2770
+ ,132.32
+ ,4490
+ ,3730
+ ,9980
+ ,2820
+ ,132.72
+ ,3480
+ ,3450
+ ,9630
+ ,3750
+ ,113.24
+ ,2520
+ ,3220
+ ,9520
+ ,3100
+ ,97.23
+ ,1920
+ ,2980
+ ,9150
+ ,4350
+ ,71.58
+ ,2010
+ ,2470
+ ,9490
+ ,4050
+ ,52.45
+ ,1950
+ ,2240
+ ,10090
+ ,6000
+ ,39.95
+ ,2240
+ ,1970
+ ,9570
+ ,10630
+ ,43.44
+ ,2370
+ ,1860
+ ,8870
+ ,3750
+ ,43.32
+ ,2840
+ ,2200
+ ,8270
+ ,3840
+ ,46.54
+ ,2700
+ ,2000
+ ,7530
+ ,4200
+ ,50.18
+ ,2980
+ ,1590
+ ,10240
+ ,2610
+ ,57.3
+ ,3290
+ ,2280
+ ,10590
+ ,2610
+ ,68.61
+ ,3300
+ ,2830
+ ,9440
+ ,2530
+ ,64.44
+ ,3000
+ ,3060
+ ,10620
+ ,3090
+ ,72.51
+ ,2330
+ ,3320
+ ,11470
+ ,4310
+ ,67.65
+ ,2190
+ ,2680
+ ,10680
+ ,4190
+ ,72.77
+ ,1970
+ ,2470
+ ,11130
+ ,3790
+ ,76.66
+ ,2170
+ ,2500
+ ,12390
+ ,3910
+ ,74.46
+ ,2830
+ ,2170
+ ,10920
+ ,4890
+ ,76.17
+ ,3190
+ ,2070
+ ,10320
+ ,4970
+ ,73.75
+ ,3550
+ ,2380
+ ,10810
+ ,5550
+ ,78.83
+ ,3240
+ ,2480
+ ,10280
+ ,4730
+ ,84.82
+ ,3450
+ ,2350
+ ,11790
+ ,4580
+ ,75.95
+ ,3570
+ ,2610
+ ,13290
+ ,2500
+ ,74.76
+ ,3230
+ ,3410
+ ,11740
+ ,2630
+ ,75.58
+ ,3260
+ ,3380
+ ,11320
+ ,4300
+ ,77.04
+ ,2700
+ ,2720
+ ,11930
+ ,3750
+ ,77.84)
+ ,dim=c(5
+ ,69)
+ ,dimnames=list(c('Garnalen'
+ ,'Kabeljauw'
+ ,'Tong'
+ ,'Zeeduivel'
+ ,'Olie')
+ ,1:69))
>  y <- array(NA,dim=c(5,69),dimnames=list(c('Garnalen','Kabeljauw','Tong','Zeeduivel','Olie'),1:69))
>  for (i in 1:dim(x)[1])
+  {
+  	for (j in 1:dim(x)[2])
+  	{
+  		y[i,j] <- as.numeric(x[i,j])
+  	}
+  }
> par4 = 'no'
> par3 = '3'
> par2 = 'none'
> par1 = '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Dr. Ian E. Holliday
> #To cite this work: Ian E. Holliday, 2009, YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: 
> #Technical description: 
> library(party)
Loading required package: survival
Loading required package: splines
Loading required package: grid
Loading required package: modeltools
Loading required package: stats4
Loading required package: coin
Loading required package: mvtnorm
Loading required package: zoo

Attaching package: 'zoo'


	The following object(s) are masked from package:base :

	 as.Date.numeric 

Loading required package: sandwich
Loading required package: strucchange
Loading required package: vcd
Loading required package: MASS
Loading required package: colorspace
> library(Hmisc)

Attaching package: 'Hmisc'


	The following object(s) are masked from package:survival :

	 untangle.specials 


	The following object(s) are masked from package:base :

	 format.pval,
	 round.POSIXt,
	 trunc.POSIXt,
	 units 

> par1 <- as.numeric(par1)
> par3 <- as.numeric(par3)
> x <- data.frame(t(y))
> is.data.frame(x)
[1] TRUE
> x <- x[!is.na(x[,par1]),]
> k <- length(x[1,])
> n <- length(x[,1])
> colnames(x)[par1]
[1] "Garnalen"
> x[,par1]
 [1]  3010  2910  3840  3580  3140  3550  3250  2820  2260  2060  2120  2210
[13]  2190  2180  2350  2440  2370  2440  2610  3040  3190  3120  3170  3600
[25]  3420  3650  4180  2960  2710  2950  3030  3770  4740  4450  5550  5580
[37]  5890  7480 10450  6360  6710  6200  4490  3480  2520  1920  2010  1950
[49]  2240  2370  2840  2700  2980  3290  3300  3000  2330  2190  1970  2170
[61]  2830  3190  3550  3240  3450  3570  3230  3260  2700
> if (par2 == 'kmeans') {
+ cl <- kmeans(x[,par1], par3)
+ print(cl)
+ clm <- matrix(cbind(cl$centers,1:par3),ncol=2)
+ clm <- clm[sort.list(clm[,1]),]
+ for (i in 1:par3) {
+ cl$cluster[cl$cluster==clm[i,2]] <- paste('C',i,sep='')
+ }
+ cl$cluster <- as.factor(cl$cluster)
+ print(cl$cluster)
+ x[,par1] <- cl$cluster
+ }
> if (par2 == 'quantiles') {
+ x[,par1] <- cut2(x[,par1],g=par3)
+ }
> if (par2 == 'hclust') {
+ hc <- hclust(dist(x[,par1])^2, 'cen')
+ print(hc)
+ memb <- cutree(hc, k = par3)
+ dum <- c(mean(x[memb==1,par1]))
+ for (i in 2:par3) {
+ dum <- c(dum, mean(x[memb==i,par1]))
+ }
+ hcm <- matrix(cbind(dum,1:par3),ncol=2)
+ hcm <- hcm[sort.list(hcm[,1]),]
+ for (i in 1:par3) {
+ memb[memb==hcm[i,2]] <- paste('C',i,sep='')
+ }
+ memb <- as.factor(memb)
+ print(memb)
+ x[,par1] <- memb
+ }
> if (par2=='equal') {
+ ed <- cut(as.numeric(x[,par1]),par3,labels=paste('C',1:par3,sep=''))
+ x[,par1] <- as.factor(ed)
+ }
> table(x[,par1])

 1920  1950  1970  2010  2060  2120  2170  2180  2190  2210  2240  2260  2330 
    1     1     1     1     1     1     1     1     2     1     1     1     1 
 2350  2370  2440  2520  2610  2700  2710  2820  2830  2840  2910  2950  2960 
    1     2     2     1     1     2     1     1     1     1     1     1     1 
 2980  3000  3010  3030  3040  3120  3140  3170  3190  3230  3240  3250  3260 
    1     1     1     1     1     1     1     1     2     1     1     1     1 
 3290  3300  3420  3450  3480  3550  3570  3580  3600  3650  3770  3840  4180 
    1     1     1     1     1     2     1     1     1     1     1     1     1 
 4450  4490  4740  5550  5580  5890  6200  6360  6710  7480 10450 
    1     1     1     1     1     1     1     1     1     1     1 
> colnames(x)
[1] "Garnalen"  "Kabeljauw" "Tong"      "Zeeduivel" "Olie"     
> colnames(x)[par1]
[1] "Garnalen"
> x[,par1]
 [1]  3010  2910  3840  3580  3140  3550  3250  2820  2260  2060  2120  2210
[13]  2190  2180  2350  2440  2370  2440  2610  3040  3190  3120  3170  3600
[25]  3420  3650  4180  2960  2710  2950  3030  3770  4740  4450  5550  5580
[37]  5890  7480 10450  6360  6710  6200  4490  3480  2520  1920  2010  1950
[49]  2240  2370  2840  2700  2980  3290  3300  3000  2330  2190  1970  2170
[61]  2830  3190  3550  3240  3450  3570  3230  3260  2700
> if (par2 == 'none') {
+ m <- ctree(as.formula(paste(colnames(x)[par1],' ~ .',sep='')),data = x)
+ }
> 
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
> 
> if (par2 != 'none') {
+ m <- ctree(as.formula(paste('as.factor(',colnames(x)[par1],') ~ .',sep='')),data = x)
+ if (par4=='yes') {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'10-Fold Cross Validation',3+2*par3,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'',1,TRUE)
+ a<-table.element(a,'Prediction (training)',par3+1,TRUE)
+ a<-table.element(a,'Prediction (testing)',par3+1,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Actual',1,TRUE)
+ for (jjj in 1:par3) a<-table.element(a,paste('C',jjj,sep=''),1,TRUE)
+ a<-table.element(a,'CV',1,TRUE)
+ for (jjj in 1:par3) a<-table.element(a,paste('C',jjj,sep=''),1,TRUE)
+ a<-table.element(a,'CV',1,TRUE)
+ a<-table.row.end(a)
+ for (i in 1:10) {
+ ind <- sample(2, nrow(x), replace=T, prob=c(0.9,0.1))
+ m.ct <- ctree(as.formula(paste('as.factor(',colnames(x)[par1],') ~ .',sep='')),data =x[ind==1,])
+ if (i==1) {
+ m.ct.i.pred <- predict(m.ct, newdata=x[ind==1,])
+ m.ct.i.actu <- x[ind==1,par1]
+ m.ct.x.pred <- predict(m.ct, newdata=x[ind==2,])
+ m.ct.x.actu <- x[ind==2,par1]
+ } else {
+ m.ct.i.pred <- c(m.ct.i.pred,predict(m.ct, newdata=x[ind==1,]))
+ m.ct.i.actu <- c(m.ct.i.actu,x[ind==1,par1])
+ m.ct.x.pred <- c(m.ct.x.pred,predict(m.ct, newdata=x[ind==2,]))
+ m.ct.x.actu <- c(m.ct.x.actu,x[ind==2,par1])
+ }
+ }
+ print(m.ct.i.tab <- table(m.ct.i.actu,m.ct.i.pred))
+ numer <- 0
+ for (i in 1:par3) {
+ print(m.ct.i.tab[i,i] / sum(m.ct.i.tab[i,]))
+ numer <- numer + m.ct.i.tab[i,i]
+ }
+ print(m.ct.i.cp <- numer / sum(m.ct.i.tab))
+ print(m.ct.x.tab <- table(m.ct.x.actu,m.ct.x.pred))
+ numer <- 0
+ for (i in 1:par3) {
+ print(m.ct.x.tab[i,i] / sum(m.ct.x.tab[i,]))
+ numer <- numer + m.ct.x.tab[i,i]
+ }
+ print(m.ct.x.cp <- numer / sum(m.ct.x.tab))
+ for (i in 1:par3) {
+ a<-table.row.start(a)
+ a<-table.element(a,paste('C',i,sep=''),1,TRUE)
+ for (jjj in 1:par3) a<-table.element(a,m.ct.i.tab[i,jjj])
+ a<-table.element(a,round(m.ct.i.tab[i,i]/sum(m.ct.i.tab[i,]),4))
+ for (jjj in 1:par3) a<-table.element(a,m.ct.x.tab[i,jjj])
+ a<-table.element(a,round(m.ct.x.tab[i,i]/sum(m.ct.x.tab[i,]),4))
+ a<-table.row.end(a)
+ }
+ a<-table.row.start(a)
+ a<-table.element(a,'Overall',1,TRUE)
+ for (jjj in 1:par3) a<-table.element(a,'-')
+ a<-table.element(a,round(m.ct.i.cp,4))
+ for (jjj in 1:par3) a<-table.element(a,'-')
+ a<-table.element(a,round(m.ct.x.cp,4))
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/rcomp/tmp/1efk51293212908.tab") 
+ }
+ }
> m

	 Conditional inference tree with 3 terminal nodes

Response:  Garnalen 
Inputs:  Kabeljauw, Tong, Zeeduivel, Olie 
Number of observations:  69 

1) Olie <= 84.82; criterion = 1, statistic = 26.691
  2) Kabeljauw <= 2720; criterion = 0.972, statistic = 7.243
    3)*  weights = 40 
  2) Kabeljauw > 2720
    4)*  weights = 18 
1) Olie > 84.82
  5)*  weights = 11 
> postscript(file="/var/www/html/rcomp/tmp/2efk51293212908.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m)
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/377jq1293212908.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(x[,par1] ~ as.factor(where(m)),main='Response by Terminal Node',xlab='Terminal Node',ylab='Response')
> dev.off()
null device 
          1 
> if (par2 == 'none') {
+ forec <- predict(m)
+ result <- as.data.frame(cbind(x[,par1],forec,x[,par1]-forec))
+ colnames(result) <- c('Actuals','Forecasts','Residuals')
+ print(result)
+ }
   Actuals Forecasts    Residuals
1     3010  2780.250   229.750000
2     2910  2780.250   129.750000
3     3840  2780.250  1059.750000
4     3580  3243.333   336.666667
5     3140  2780.250   359.750000
6     3550  2780.250   769.750000
7     3250  2780.250   469.750000
8     2820  2780.250    39.750000
9     2260  2780.250  -520.250000
10    2060  2780.250  -720.250000
11    2120  2780.250  -660.250000
12    2210  2780.250  -570.250000
13    2190  2780.250  -590.250000
14    2180  2780.250  -600.250000
15    2350  2780.250  -430.250000
16    2440  3243.333  -803.333333
17    2370  2780.250  -410.250000
18    2440  2780.250  -340.250000
19    2610  2780.250  -170.250000
20    3040  3243.333  -203.333333
21    3190  3243.333   -53.333333
22    3120  3243.333  -123.333333
23    3170  2780.250   389.750000
24    3600  3243.333   356.666667
25    3420  3243.333   176.666667
26    3650  2780.250   869.750000
27    4180  2780.250  1399.750000
28    2960  3243.333  -283.333333
29    2710  2780.250   -70.250000
30    2950  2780.250   169.750000
31    3030  3243.333  -213.333333
32    3770  3243.333   526.666667
33    4740  3243.333  1496.666667
34    4450  3243.333  1206.666667
35    5550  5882.727  -332.727273
36    5580  5882.727  -302.727273
37    5890  5882.727     7.272727
38    7480  5882.727  1597.272727
39   10450  5882.727  4567.272727
40    6360  5882.727   477.272727
41    6710  5882.727   827.272727
42    6200  5882.727   317.272727
43    4490  5882.727 -1392.727273
44    3480  5882.727 -2402.727273
45    2520  5882.727 -3362.727273
46    1920  3243.333 -1323.333333
47    2010  2780.250  -770.250000
48    1950  2780.250  -830.250000
49    2240  2780.250  -540.250000
50    2370  2780.250  -410.250000
51    2840  2780.250    59.750000
52    2700  2780.250   -80.250000
53    2980  2780.250   199.750000
54    3290  2780.250   509.750000
55    3300  3243.333    56.666667
56    3000  3243.333  -243.333333
57    2330  3243.333  -913.333333
58    2190  2780.250  -590.250000
59    1970  2780.250  -810.250000
60    2170  2780.250  -610.250000
61    2830  2780.250    49.750000
62    3190  2780.250   409.750000
63    3550  2780.250   769.750000
64    3240  2780.250   459.750000
65    3450  2780.250   669.750000
66    3570  2780.250   789.750000
67    3230  3243.333   -13.333333
68    3260  3243.333    16.666667
69    2700  2780.250   -80.250000
> if (par2 != 'none') {
+ print(cbind(as.factor(x[,par1]),predict(m)))
+ myt <- table(as.factor(x[,par1]),predict(m))
+ print(myt)
+ }
> postscript(file="/var/www/html/rcomp/tmp/4zyjb1293212908.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if(par2=='none') {
+ op <- par(mfrow=c(2,2))
+ plot(density(result$Actuals),main='Kernel Density Plot of Actuals')
+ plot(density(result$Residuals),main='Kernel Density Plot of Residuals')
+ plot(result$Forecasts,result$Actuals,main='Actuals versus Predictions',xlab='Predictions',ylab='Actuals')
+ plot(density(result$Forecasts),main='Kernel Density Plot of Predictions')
+ par(op)
+ }
> if(par2!='none') {
+ plot(myt,main='Confusion Matrix',xlab='Actual',ylab='Predicted')
+ }
> dev.off()
null device 
          1 
> if (par2 == 'none') {
+ detcoef <- cor(result$Forecasts,result$Actuals)
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Goodness of Fit',2,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Correlation',1,TRUE)
+ a<-table.element(a,round(detcoef,4))
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'R-squared',1,TRUE)
+ a<-table.element(a,round(detcoef*detcoef,4))
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'RMSE',1,TRUE)
+ a<-table.element(a,round(sqrt(mean((result$Residuals)^2)),4))
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/rcomp/tmp/5kghh1293212908.tab") 
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Actuals, Predictions, and Residuals',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'#',header=TRUE)
+ a<-table.element(a,'Actuals',header=TRUE)
+ a<-table.element(a,'Forecasts',header=TRUE)
+ a<-table.element(a,'Residuals',header=TRUE)
+ a<-table.row.end(a)
+ for (i in 1:length(result$Actuals)) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,result$Actuals[i])
+ a<-table.element(a,result$Forecasts[i])
+ a<-table.element(a,result$Residuals[i])
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/rcomp/tmp/6ohfn1293212908.tab") 
+ }
> if (par2 != 'none') {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Confusion Matrix (predicted in columns / actuals in rows)',par3+1,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'',1,TRUE)
+ for (i in 1:par3) {
+ a<-table.element(a,paste('C',i,sep=''),1,TRUE)
+ }
+ a<-table.row.end(a)
+ for (i in 1:par3) {
+ a<-table.row.start(a)
+ a<-table.element(a,paste('C',i,sep=''),1,TRUE)
+ for (j in 1:par3) {
+ a<-table.element(a,myt[i,j])
+ }
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/rcomp/tmp/7hqxq1293212908.tab") 
+ }
> 
> try(system("convert tmp/2efk51293212908.ps tmp/2efk51293212908.png",intern=TRUE))
character(0)
> try(system("convert tmp/377jq1293212908.ps tmp/377jq1293212908.png",intern=TRUE))
character(0)
> try(system("convert tmp/4zyjb1293212908.ps tmp/4zyjb1293212908.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.206   0.591   6.813