R version 3.2.3 (2015-12-10) -- "Wooden Christmas-Tree"
Copyright (C) 2015 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(98.72,98.67,98.82,99.39,99.33,99.22,99.05,98.83,98.84,98.89,98.8,99.4,98.89,98.85,98.69,98.48,98.39,98.35,98.26,98.06,98.14,98.17,98.41,98.64,99.25,99.61,100.28,100.31,100.55,100.45,100.78,100.68,101.69,98.09,99.13,99.18,96.22,96.11,96,95.96,97.95,98.43,98.32,97.45,96.42,95.36,95.1,95.54,94.07,93.48,92.86,90.98,91.45,91.16,90.71,90.31,89.78,91.02,90.77,90.69)
> par1 = '60'
> par1 <- as.numeric(par1)
> x <- na.omit(x)
> (n <- length(x))
[1] 60
> (np <- floor(n / par1))
[1] 1
> arr <- array(NA,dim=c(par1,np+1))
> darr <- array(NA,dim=c(par1,np+1))
> ari <- array(0,dim=par1)
> dx <- diff(x)
> j <- 0
> for (i in 1:n)
+ {
+ j = j + 1
+ ari[j] = ari[j] + 1
+ arr[j,ari[j]] <- x[i]
+ darr[j,ari[j]] <- dx[i]
+ if (j == par1) j = 0
+ }
> ari
 [1] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
[39] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
> arr
        [,1] [,2]
 [1,]  98.72   NA
 [2,]  98.67   NA
 [3,]  98.82   NA
 [4,]  99.39   NA
 [5,]  99.33   NA
 [6,]  99.22   NA
 [7,]  99.05   NA
 [8,]  98.83   NA
 [9,]  98.84   NA
[10,]  98.89   NA
[11,]  98.80   NA
[12,]  99.40   NA
[13,]  98.89   NA
[14,]  98.85   NA
[15,]  98.69   NA
[16,]  98.48   NA
[17,]  98.39   NA
[18,]  98.35   NA
[19,]  98.26   NA
[20,]  98.06   NA
[21,]  98.14   NA
[22,]  98.17   NA
[23,]  98.41   NA
[24,]  98.64   NA
[25,]  99.25   NA
[26,]  99.61   NA
[27,] 100.28   NA
[28,] 100.31   NA
[29,] 100.55   NA
[30,] 100.45   NA
[31,] 100.78   NA
[32,] 100.68   NA
[33,] 101.69   NA
[34,]  98.09   NA
[35,]  99.13   NA
[36,]  99.18   NA
[37,]  96.22   NA
[38,]  96.11   NA
[39,]  96.00   NA
[40,]  95.96   NA
[41,]  97.95   NA
[42,]  98.43   NA
[43,]  98.32   NA
[44,]  97.45   NA
[45,]  96.42   NA
[46,]  95.36   NA
[47,]  95.10   NA
[48,]  95.54   NA
[49,]  94.07   NA
[50,]  93.48   NA
[51,]  92.86   NA
[52,]  90.98   NA
[53,]  91.45   NA
[54,]  91.16   NA
[55,]  90.71   NA
[56,]  90.31   NA
[57,]  89.78   NA
[58,]  91.02   NA
[59,]  90.77   NA
[60,]  90.69   NA
> darr
       [,1] [,2]
 [1,] -0.05   NA
 [2,]  0.15   NA
 [3,]  0.57   NA
 [4,] -0.06   NA
 [5,] -0.11   NA
 [6,] -0.17   NA
 [7,] -0.22   NA
 [8,]  0.01   NA
 [9,]  0.05   NA
[10,] -0.09   NA
[11,]  0.60   NA
[12,] -0.51   NA
[13,] -0.04   NA
[14,] -0.16   NA
[15,] -0.21   NA
[16,] -0.09   NA
[17,] -0.04   NA
[18,] -0.09   NA
[19,] -0.20   NA
[20,]  0.08   NA
[21,]  0.03   NA
[22,]  0.24   NA
[23,]  0.23   NA
[24,]  0.61   NA
[25,]  0.36   NA
[26,]  0.67   NA
[27,]  0.03   NA
[28,]  0.24   NA
[29,] -0.10   NA
[30,]  0.33   NA
[31,] -0.10   NA
[32,]  1.01   NA
[33,] -3.60   NA
[34,]  1.04   NA
[35,]  0.05   NA
[36,] -2.96   NA
[37,] -0.11   NA
[38,] -0.11   NA
[39,] -0.04   NA
[40,]  1.99   NA
[41,]  0.48   NA
[42,] -0.11   NA
[43,] -0.87   NA
[44,] -1.03   NA
[45,] -1.06   NA
[46,] -0.26   NA
[47,]  0.44   NA
[48,] -1.47   NA
[49,] -0.59   NA
[50,] -0.62   NA
[51,] -1.88   NA
[52,]  0.47   NA
[53,] -0.29   NA
[54,] -0.45   NA
[55,] -0.40   NA
[56,] -0.53   NA
[57,]  1.24   NA
[58,] -0.25   NA
[59,] -0.08   NA
[60,]    NA   NA
> arr.mean <- array(NA,dim=par1)
> arr.median <- array(NA,dim=par1)
> arr.midrange <- array(NA,dim=par1)
> for (j in 1:par1)
+ {
+ arr.mean[j] <- mean(arr[j,],na.rm=TRUE)
+ arr.median[j] <- median(arr[j,],na.rm=TRUE)
+ arr.midrange[j] <- (quantile(arr[j,],0.75,na.rm=TRUE) + quantile(arr[j,],0.25,na.rm=TRUE)) / 2
+ }
> overall.mean <- mean(x)
> overall.median <- median(x)
> overall.midrange <- (quantile(x,0.75) + quantile(x,0.25)) / 2
> postscript(file="/var/wessaorg/rcomp/tmp/13c191457180734.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(arr.mean,type='b',ylab='mean',main='Mean Plot',xlab='Periodic Index')
> mtext(paste('#blocks = ',np))
> abline(overall.mean,0)
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/2204t1457180734.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(arr.median,type='b',ylab='median',main='Median Plot',xlab='Periodic Index')
> mtext(paste('#blocks = ',np))
> abline(overall.median,0)
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/3e88t1457180734.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(arr.midrange,type='b',ylab='midrange',main='Midrange Plot',xlab='Periodic Index')
> mtext(paste('#blocks = ',np))
> abline(overall.midrange,0)
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/4ezz31457180734.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> z <- data.frame(t(arr))
> names(z) <- c(1:par1)
> (boxplot(z,notch=TRUE,col='grey',xlab='Periodic Index',ylab='Value',main='Notched Box Plots - Periodic Subseries'))
$stats
      [,1]  [,2]  [,3]  [,4]  [,5]  [,6]  [,7]  [,8]  [,9] [,10] [,11] [,12]
[1,] 98.72 98.67 98.82 99.39 99.33 99.22 99.05 98.83 98.84 98.89  98.8  99.4
[2,] 98.72 98.67 98.82 99.39 99.33 99.22 99.05 98.83 98.84 98.89  98.8  99.4
[3,] 98.72 98.67 98.82 99.39 99.33 99.22 99.05 98.83 98.84 98.89  98.8  99.4
[4,] 98.72 98.67 98.82 99.39 99.33 99.22 99.05 98.83 98.84 98.89  98.8  99.4
[5,] 98.72 98.67 98.82 99.39 99.33 99.22 99.05 98.83 98.84 98.89  98.8  99.4
     [,13] [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24]
[1,] 98.89 98.85 98.69 98.48 98.39 98.35 98.26 98.06 98.14 98.17 98.41 98.64
[2,] 98.89 98.85 98.69 98.48 98.39 98.35 98.26 98.06 98.14 98.17 98.41 98.64
[3,] 98.89 98.85 98.69 98.48 98.39 98.35 98.26 98.06 98.14 98.17 98.41 98.64
[4,] 98.89 98.85 98.69 98.48 98.39 98.35 98.26 98.06 98.14 98.17 98.41 98.64
[5,] 98.89 98.85 98.69 98.48 98.39 98.35 98.26 98.06 98.14 98.17 98.41 98.64
     [,25] [,26]  [,27]  [,28]  [,29]  [,30]  [,31]  [,32]  [,33] [,34] [,35]
[1,] 99.25 99.61 100.28 100.31 100.55 100.45 100.78 100.68 101.69 98.09 99.13
[2,] 99.25 99.61 100.28 100.31 100.55 100.45 100.78 100.68 101.69 98.09 99.13
[3,] 99.25 99.61 100.28 100.31 100.55 100.45 100.78 100.68 101.69 98.09 99.13
[4,] 99.25 99.61 100.28 100.31 100.55 100.45 100.78 100.68 101.69 98.09 99.13
[5,] 99.25 99.61 100.28 100.31 100.55 100.45 100.78 100.68 101.69 98.09 99.13
     [,36] [,37] [,38] [,39] [,40] [,41] [,42] [,43] [,44] [,45] [,46] [,47]
[1,] 99.18 96.22 96.11    96 95.96 97.95 98.43 98.32 97.45 96.42 95.36  95.1
[2,] 99.18 96.22 96.11    96 95.96 97.95 98.43 98.32 97.45 96.42 95.36  95.1
[3,] 99.18 96.22 96.11    96 95.96 97.95 98.43 98.32 97.45 96.42 95.36  95.1
[4,] 99.18 96.22 96.11    96 95.96 97.95 98.43 98.32 97.45 96.42 95.36  95.1
[5,] 99.18 96.22 96.11    96 95.96 97.95 98.43 98.32 97.45 96.42 95.36  95.1
     [,48] [,49] [,50] [,51] [,52] [,53] [,54] [,55] [,56] [,57] [,58] [,59]
[1,] 95.54 94.07 93.48 92.86 90.98 91.45 91.16 90.71 90.31 89.78 91.02 90.77
[2,] 95.54 94.07 93.48 92.86 90.98 91.45 91.16 90.71 90.31 89.78 91.02 90.77
[3,] 95.54 94.07 93.48 92.86 90.98 91.45 91.16 90.71 90.31 89.78 91.02 90.77
[4,] 95.54 94.07 93.48 92.86 90.98 91.45 91.16 90.71 90.31 89.78 91.02 90.77
[5,] 95.54 94.07 93.48 92.86 90.98 91.45 91.16 90.71 90.31 89.78 91.02 90.77
     [,60]
[1,] 90.69
[2,] 90.69
[3,] 90.69
[4,] 90.69
[5,] 90.69

$n
 [1] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
[39] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

$conf
      [,1]  [,2]  [,3]  [,4]  [,5]  [,6]  [,7]  [,8]  [,9] [,10] [,11] [,12]
[1,] 98.72 98.67 98.82 99.39 99.33 99.22 99.05 98.83 98.84 98.89  98.8  99.4
[2,] 98.72 98.67 98.82 99.39 99.33 99.22 99.05 98.83 98.84 98.89  98.8  99.4
     [,13] [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24]
[1,] 98.89 98.85 98.69 98.48 98.39 98.35 98.26 98.06 98.14 98.17 98.41 98.64
[2,] 98.89 98.85 98.69 98.48 98.39 98.35 98.26 98.06 98.14 98.17 98.41 98.64
     [,25] [,26]  [,27]  [,28]  [,29]  [,30]  [,31]  [,32]  [,33] [,34] [,35]
[1,] 99.25 99.61 100.28 100.31 100.55 100.45 100.78 100.68 101.69 98.09 99.13
[2,] 99.25 99.61 100.28 100.31 100.55 100.45 100.78 100.68 101.69 98.09 99.13
     [,36] [,37] [,38] [,39] [,40] [,41] [,42] [,43] [,44] [,45] [,46] [,47]
[1,] 99.18 96.22 96.11    96 95.96 97.95 98.43 98.32 97.45 96.42 95.36  95.1
[2,] 99.18 96.22 96.11    96 95.96 97.95 98.43 98.32 97.45 96.42 95.36  95.1
     [,48] [,49] [,50] [,51] [,52] [,53] [,54] [,55] [,56] [,57] [,58] [,59]
[1,] 95.54 94.07 93.48 92.86 90.98 91.45 91.16 90.71 90.31 89.78 91.02 90.77
[2,] 95.54 94.07 93.48 92.86 90.98 91.45 91.16 90.71 90.31 89.78 91.02 90.77
     [,60]
[1,] 90.69
[2,] 90.69

$out
numeric(0)

$group
numeric(0)

$names
 [1] "1"  "2"  "3"  "4"  "5"  "6"  "7"  "8"  "9"  "10" "11" "12" "13" "14" "15"
[16] "16" "17" "18" "19" "20" "21" "22" "23" "24" "25" "26" "27" "28" "29" "30"
[31] "31" "32" "33" "34" "35" "36" "37" "38" "39" "40" "41" "42" "43" "44" "45"
[46] "46" "47" "48" "49" "50" "51" "52" "53" "54" "55" "56" "57" "58" "59" "60"

> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/579ee1457180734.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> z <- data.frame(t(darr))
> names(z) <- c(1:par1)
> (boxplot(z,notch=TRUE,col='grey',xlab='Periodic Index',ylab='Value',main='Notched Box Plots - Differenced Periodic Subseries'))
$stats
      [,1] [,2] [,3]  [,4]  [,5]  [,6]  [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] -0.05 0.15 0.57 -0.06 -0.11 -0.17 -0.22 0.01 0.05 -0.09   0.6 -0.51 -0.04
[2,] -0.05 0.15 0.57 -0.06 -0.11 -0.17 -0.22 0.01 0.05 -0.09   0.6 -0.51 -0.04
[3,] -0.05 0.15 0.57 -0.06 -0.11 -0.17 -0.22 0.01 0.05 -0.09   0.6 -0.51 -0.04
[4,] -0.05 0.15 0.57 -0.06 -0.11 -0.17 -0.22 0.01 0.05 -0.09   0.6 -0.51 -0.04
[5,] -0.05 0.15 0.57 -0.06 -0.11 -0.17 -0.22 0.01 0.05 -0.09   0.6 -0.51 -0.04
     [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
[1,] -0.16 -0.21 -0.09 -0.04 -0.09  -0.2  0.08  0.03  0.24  0.23  0.61  0.36
[2,] -0.16 -0.21 -0.09 -0.04 -0.09  -0.2  0.08  0.03  0.24  0.23  0.61  0.36
[3,] -0.16 -0.21 -0.09 -0.04 -0.09  -0.2  0.08  0.03  0.24  0.23  0.61  0.36
[4,] -0.16 -0.21 -0.09 -0.04 -0.09  -0.2  0.08  0.03  0.24  0.23  0.61  0.36
[5,] -0.16 -0.21 -0.09 -0.04 -0.09  -0.2  0.08  0.03  0.24  0.23  0.61  0.36
     [,26] [,27] [,28] [,29] [,30] [,31] [,32] [,33] [,34] [,35] [,36] [,37]
[1,]  0.67  0.03  0.24  -0.1  0.33  -0.1  1.01  -3.6  1.04  0.05 -2.96 -0.11
[2,]  0.67  0.03  0.24  -0.1  0.33  -0.1  1.01  -3.6  1.04  0.05 -2.96 -0.11
[3,]  0.67  0.03  0.24  -0.1  0.33  -0.1  1.01  -3.6  1.04  0.05 -2.96 -0.11
[4,]  0.67  0.03  0.24  -0.1  0.33  -0.1  1.01  -3.6  1.04  0.05 -2.96 -0.11
[5,]  0.67  0.03  0.24  -0.1  0.33  -0.1  1.01  -3.6  1.04  0.05 -2.96 -0.11
     [,38] [,39] [,40] [,41] [,42] [,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.11 -0.04  1.99  0.48 -0.11 -0.87 -1.03 -1.06 -0.26  0.44 -1.47 -0.59
[2,] -0.11 -0.04  1.99  0.48 -0.11 -0.87 -1.03 -1.06 -0.26  0.44 -1.47 -0.59
[3,] -0.11 -0.04  1.99  0.48 -0.11 -0.87 -1.03 -1.06 -0.26  0.44 -1.47 -0.59
[4,] -0.11 -0.04  1.99  0.48 -0.11 -0.87 -1.03 -1.06 -0.26  0.44 -1.47 -0.59
[5,] -0.11 -0.04  1.99  0.48 -0.11 -0.87 -1.03 -1.06 -0.26  0.44 -1.47 -0.59
     [,50] [,51] [,52] [,53] [,54] [,55] [,56] [,57] [,58] [,59] [,60]
[1,] -0.62 -1.88  0.47 -0.29 -0.45  -0.4 -0.53  1.24 -0.25 -0.08    NA
[2,] -0.62 -1.88  0.47 -0.29 -0.45  -0.4 -0.53  1.24 -0.25 -0.08    NA
[3,] -0.62 -1.88  0.47 -0.29 -0.45  -0.4 -0.53  1.24 -0.25 -0.08    NA
[4,] -0.62 -1.88  0.47 -0.29 -0.45  -0.4 -0.53  1.24 -0.25 -0.08    NA
[5,] -0.62 -1.88  0.47 -0.29 -0.45  -0.4 -0.53  1.24 -0.25 -0.08    NA

$n
 [1] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
[39] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0

$conf
      [,1] [,2] [,3]  [,4]  [,5]  [,6]  [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] -0.05 0.15 0.57 -0.06 -0.11 -0.17 -0.22 0.01 0.05 -0.09   0.6 -0.51 -0.04
[2,] -0.05 0.15 0.57 -0.06 -0.11 -0.17 -0.22 0.01 0.05 -0.09   0.6 -0.51 -0.04
     [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
[1,] -0.16 -0.21 -0.09 -0.04 -0.09  -0.2  0.08  0.03  0.24  0.23  0.61  0.36
[2,] -0.16 -0.21 -0.09 -0.04 -0.09  -0.2  0.08  0.03  0.24  0.23  0.61  0.36
     [,26] [,27] [,28] [,29] [,30] [,31] [,32] [,33] [,34] [,35] [,36] [,37]
[1,]  0.67  0.03  0.24  -0.1  0.33  -0.1  1.01  -3.6  1.04  0.05 -2.96 -0.11
[2,]  0.67  0.03  0.24  -0.1  0.33  -0.1  1.01  -3.6  1.04  0.05 -2.96 -0.11
     [,38] [,39] [,40] [,41] [,42] [,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.11 -0.04  1.99  0.48 -0.11 -0.87 -1.03 -1.06 -0.26  0.44 -1.47 -0.59
[2,] -0.11 -0.04  1.99  0.48 -0.11 -0.87 -1.03 -1.06 -0.26  0.44 -1.47 -0.59
     [,50] [,51] [,52] [,53] [,54] [,55] [,56] [,57] [,58] [,59] [,60]
[1,] -0.62 -1.88  0.47 -0.29 -0.45  -0.4 -0.53  1.24 -0.25 -0.08    NA
[2,] -0.62 -1.88  0.47 -0.29 -0.45  -0.4 -0.53  1.24 -0.25 -0.08    NA

$out
numeric(0)

$group
numeric(0)

$names
 [1] "1"  "2"  "3"  "4"  "5"  "6"  "7"  "8"  "9"  "10" "11" "12" "13" "14" "15"
[16] "16" "17" "18" "19" "20" "21" "22" "23" "24" "25" "26" "27" "28" "29" "30"
[31] "31" "32" "33" "34" "35" "36" "37" "38" "39" "40" "41" "42" "43" "44" "45"
[46] "46" "47" "48" "49" "50" "51" "52" "53" "54" "55" "56" "57" "58" "59" "60"

> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/6z8k81457180734.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> z <- data.frame(arr)
> names(z) <- c(1:np)
> (boxplot(z,notch=TRUE,col='grey',xlab='Block Index',ylab='Value',main='Notched Box Plots - Sequential Blocks'))
$stats
       [,1] [,2]
[1,]  90.77   NA
[2,]  95.75   NA
[3,]  98.40   NA
[4,]  99.09   NA
[5,] 101.69   NA

$n
[1] 60  0

$conf
         [,1] [,2]
[1,] 97.71872   NA
[2,] 99.08128   NA

$out
[1] 90.71 90.31 89.78 90.69

$group
[1] 1 1 1 1

$names
[1] "1" NA 

> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/70mdz1457180734.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> z <- data.frame(cbind(arr.mean,arr.median,arr.midrange))
> names(z) <- list('mean','median','midrange')
> (boxplot(z,notch=TRUE,col='grey',ylab='Overall Central Tendency',main='Notched Box Plots'))
$stats
       [,1]   [,2]   [,3]
[1,]  90.77  90.77  90.77
[2,]  95.75  95.75  95.75
[3,]  98.40  98.40  98.40
[4,]  99.09  99.09  99.09
[5,] 101.69 101.69 101.69

$n
[1] 60 60 60

$conf
         [,1]     [,2]     [,3]
[1,] 97.71872 97.71872 97.71872
[2,] 99.08128 99.08128 99.08128

$out
 [1] 90.71 90.31 89.78 90.69 90.71 90.31 89.78 90.69 90.71 90.31 89.78 90.69

$group
 [1] 1 1 1 1 2 2 2 2 3 3 3 3

$names
[1] "mean"     "median"   "midrange"

> dev.off()
null device 
          1 
> 
> try(system("convert tmp/13c191457180734.ps tmp/13c191457180734.png",intern=TRUE))
character(0)
> try(system("convert tmp/2204t1457180734.ps tmp/2204t1457180734.png",intern=TRUE))
character(0)
> try(system("convert tmp/3e88t1457180734.ps tmp/3e88t1457180734.png",intern=TRUE))
character(0)
> try(system("convert tmp/4ezz31457180734.ps tmp/4ezz31457180734.png",intern=TRUE))
character(0)
> try(system("convert tmp/579ee1457180734.ps tmp/579ee1457180734.png",intern=TRUE))
character(0)
> try(system("convert tmp/6z8k81457180734.ps tmp/6z8k81457180734.png",intern=TRUE))
character(0)
> try(system("convert tmp/70mdz1457180734.ps tmp/70mdz1457180734.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.429   0.409   2.863