Dear Jim,
It works, nonetheless, it doesn't slip the screen correctly :(
Do you have any idea?
I used the code:
#setwd("/Users/RO/Dropbox/LMER -
3rdproblem/R/latest_version/graphs/data")
setwd("~/Dropbox/LMER - 3rdproblem/R/latest_version/graphs/data")
library(ggplot2)
library(reshape)
library(lattice)
# read in what looks like half of the data
bias.alpha2<-read.csv("graphs_bias_alpha2.csv")
SE.alpha2<-read.csv("graphs_SE_alpha2.csv")
bias.alpha1<-read.csv("graphs_bias_alpha1.csv")
SE.alpha1<-read.csv("graphs_SE_alpha1.csv")
quartz(width=10,height=6)
# do the first split, to get the rightmost screen for the legend
split.screen(figs=matrix(c(0,0.84,0,1,0.84,1,0,1),nrow=2,byrow=TRUE))
# now split the first screen to get your eight screens (numbered 3 to 10)
for the plots
split.screen(figs=matrix(c(0,0.25,0.5,1,
0.25,0.5,0.5,1,
0.5,0.75,0.5,1,
0.75,1,0.5,1,
0,0.25,0,0.5,
0.25,0.5,0,0.5,
0.5,0.75,0,0.5,
0.75,1,0,0.5),
ncol=4,byrow=TRUE),screen=1)
#split.screen(figs=matrix(c(0,0.5,0.5,1,#primeira linha primeira coluna
# 0.5,1,0.5,1,#primeira linha segunda coluna
# 0,0.5,0,0.5,#segunda linha primeira coluna
# 0.5,1,0,0.5),#segunda linha segunda coluna
# ncol=4,byrow=TRUE),screen=1)
# this produces seven screens numbered like this:
# 3 4 5 6
# 2
# 7 8 9 10
# select the upper left screen
screen(3)
par(mar=c(0,3.5,3,0))
# now the second set
n250<-bias.alpha1$nsample==250
matplot(x=bias.alpha1$lambda[n250],y=bias.alpha1[n250,3:5],
type="l",pch=1:3,col=c(4,2,3),xaxt="n",ylim=c(-.1,
.6),main="nsample=250",ylab="", cex.main=1)
abline(h = 0, col = "gray60")
mtext(expression(paste("Bias av. for ",alpha[1])),side=2,line=2,
cex.main=1)
screen(4)
par(mar=c(0,0,3,0))
# now the second set
n1000<-bias.alpha1$nsample==1000
matplot(x=bias.alpha1$lambda[n1000],y=bias.alpha1[n1000,3:5],
type="l",pch=1:3,col=c(4,2,3),xaxt="n",yaxt="n",ylim=c(-.1,
.6),main="nsample=1000",ylab="")
abline(h = 0, col = "gray60")
screen(5)
par(mar=c(0,3.5,3,0))
# now the second set
par(mar=c(3,3.5,0,0))
# now the second set
n250<-bias.alpha2$nsample==250
matplot(x=bias.alpha2$lambda[n250],y=bias.alpha2[n250,3:5],
type="l",pch=1:3,col=c(4,2,3),ylim=c(-.1,
.6),ylab="")
abline(h = 0, col = "gray60")
mtext(expression(paste("Bias av. for ",alpha[2])),side=2,line=2,
cex.main=1.5)
screen(6)
par(mar=c(3,0,0,0))
# now the second set
n1000<-bias.alpha2$nsample==1000
matplot(x=bias.alpha2$lambda[n1000],y=bias.alpha2[n1000,3:5],
type="l",pch=1:3,col=c(4,2,3),yaxt="n",ylim=c(-.1,
.6))
abline(h = 0, col = "gray60")
screen(7)
par(mar=c(0,3.5,3,0))
# now the second set
n250<-SE.alpha1$nsample==250
matplot(x=SE.alpha1$lambda[n250],y=SE.alpha1[n250,3:5],
type="l",pch=1:3,col=c(4,2,3),xaxt="n",ylim=c(0,
1.1),main="nsample=250",ylab="", cex.main=1)
abline(h = -1, col = "gray60")
mtext(expression(paste("SE av. for ",alpha[1])),side=2,line=2,
cex.main=1)
mtext(expression(paste(lambda)),side=1,line=2, cex.main=1.5)
screen(8)
par(mar=c(0,0,3,0))
# now the second set
n1000<-SE.alpha1$nsample==1000
matplot(x=SE.alpha1$lambda[n1000],y=SE.alpha1[n1000,3:5],
type="l",pch=1:3,col=c(4,2,3),xaxt="n",yaxt="n",ylim=c(0,
1.1),main="nsample=1000",ylab="")
abline(h = -1, col = "gray60")
screen(9)
par(mar=c(3,3.5,0,0))
# now the second set
n250<-SE.alpha2$nsample==250
matplot(x=SE.alpha2$lambda[n250],y=SE.alpha2[n250,3:5],
type="l",pch=1:3,col=c(4,2,3),ylim=c(0,
1.1),ylab="")
abline(h = -.5, col = "gray60")
mtext(expression(paste("SE av. for ",alpha[2])),side=2,line=2,
cex.main=1.5)
mtext(expression(paste(lambda)),side=1,line=2, cex.main=1.5)
screen(10)
par(mar=c(3,0,0,0))
# now the second set
n1000<-SE.alpha2$nsample==1000
matplot(x=SE.alpha2$lambda[n1000],y=SE.alpha2[n1000,3:5],
type="l",pch=1:3,col=c(4,2,3),yaxt="n",ylim=c(0,
1.1))
abline(h = -.5, col = "gray60")
mtext(expression(paste(lambda)),side=1,line=2, , cex.main=1.5)
screen(2)
par(mar=c(0,0,0,0))
# plot an empty plot to get the coordinates
plot(0:1,0:1,type="n",axes=FALSE)
legend(0,0.6,c("OLS", "GLS", "Reg. Cal.",
"0"),bty = "n",
lty=1:3,col=c(4,2,3,"gray60"),xpd=TRUE)
close.screen(all=TRUE)
and I attach the output graph.
Best,
RO
Atenciosamente,
Rosa Oliveira
_________________________________
Antes de imprimir este e-mail pense bem se tem mesmo que o fazer.
H? cada vez menos ?rvores.
N?o imprima, pense na sua responsabilidade e compromisso com o MEIO
AMBIENTE!
<http://pt.dreamstime.com/cora-ccedil-atildeo-criado-das-folhas-de-aacutervores-diferentes-thumb12275776.jpg>
<http://pt.dreamstime.com/cora-ccedil-atildeo-criado-das-folhas-de-aacutervores-diferentes-thumb12275776.jpg>
2015-09-17 12:18 GMT+01:00 Jim Lemon <drjimlemon at gmail.com>:
> Hi Rosa,
> Try this:
>
> # do the first split, to get the rightmost screen for the legend
> split.screen(figs=matrix(c(0,0.84,0,1,0.84,1,0,1),nrow=2,byrow=TRUE))
> # now split the first screen to get your eight screens (numbered 3 to 10)
> for the plots
> split.screen(figs=matrix(c(0,0.25,0.5,1,
> 0.25,0.5,0.5,1,
> 0.5,0.75,0.5,1,
> 0.75,1,0.5,1,
> 0,0.25,0,0.5,
> 0.25,0.5,0,0.5,
> 0.5,0.75,0,0.5,
> 0.75,1,0,0.5),
> ncol=4,byrow=TRUE),screen=1)
>
> Jim
>
>
> On Thu, Sep 17, 2015 at 2:45 AM, Rosa Oliveira <rosita21 at
gmail.com> wrote:
>
>> Dear all,
>>
>> I?m trying to do a graph,
>>
>> 3 rows, 5 columns, with the design:
>> # 3 4 5 6
>> # 2
>> # 7 8 9 10
>>
>> I had a code for 3 rows, 3 columns, with the design::
>> # 3 4
>> # 2
>> # 7 8
>> and I tried to modify it, but I had no success :(
>>
>> I suppose the problem is in the slip.screen code (red part of the
code).
>>
>> I attach my code, can anyone please help me?
>>
>>
>> Best,
>> RO
>>
>>
>> setwd("/Users/RO/Dropbox/LMER -
3rdproblem/R/latest_version/graphs/data")
>>
>> library(ggplot2)
>> library(reshape)
>> library(lattice)
>>
>>
>> # read in what looks like half of the data
>>
>> bias.alpha2<-read.csv("graphs_bias_alpha2.csv")
>> SE.alpha2<-read.csv("graphs_SE_alpha2.csv")
>> bias.alpha1<-read.csv("graphs_bias_alpha1.csv")
>> SE.alpha1<-read.csv("graphs_SE_alpha1.csv")
>>
>>
>>
>> quartz(width=10,height=6)
>> # do the first split, to get the rightmost screen for the legend
>> split.screen(figs=matrix(c(0,0.8,0,1,0.8,1,0,1),nrow=2,byrow=TRUE))
>> # now split the first screen to get your six screens for the plots
>>
>>
>>
>> split.screen(figs=matrix(c(0,0.5,0.5,1,#primeira linha primeira coluna
>> 0.5,1,0.5,1,#primeira linha segunda coluna
>> 0,0.5,0,0.5,#segunda linha primeira coluna
>> 0.5,1,0,0.5),#segunda linha segunda coluna
>> ncol=4,byrow=TRUE),screen=1)
>>
>>
>> # this produces seven screens numbered like this:
>> # 3 4 5 6
>> # 2
>> # 7 8 9 10
>> # select the upper left screen
>>
>>
>>
>> screen(3)
>> par(mar=c(0,3.5,3,0))
>> # now the second set
>> n250<-bias.alpha1$nsample==250
>> matplot(x=bias.alpha1$lambda[n250],y=bias.alpha1[n250,3:5],
>>
type="l",pch=1:3,col=c(4,2,3),xaxt="n",ylim=c(-.1,
>> .6),main="nsample=250",ylab="", cex.main=1)
>> abline(h = 0, col = "gray60")
>> mtext(expression(paste("Bias av. for
",alpha[1])),side=2,line=2,
>> cex.main=1)
>>
>> screen(4)
>> par(mar=c(0,0,3,0))
>> # now the second set
>> n1000<-bias.alpha1$nsample==1000
>> matplot(x=bias.alpha1$lambda[n1000],y=bias.alpha1[n1000,3:5],
>>
type="l",pch=1:3,col=c(4,2,3),xaxt="n",yaxt="n",ylim=c(-.1,
>> .6),main="nsample=1000",ylab="")
>> abline(h = 0, col = "gray60")
>>
>>
>>
>> screen(5)
>> par(mar=c(0,3.5,3,0))
>> # now the second set
>> par(mar=c(3,3.5,0,0))
>> # now the second set
>> n250<-bias.alpha2$nsample==250
>> matplot(x=bias.alpha2$lambda[n250],y=bias.alpha2[n250,3:5],
>> type="l",pch=1:3,col=c(4,2,3),ylim=c(-.1,
.6),ylab="")
>> abline(h = 0, col = "gray60")
>> mtext(expression(paste("Bias av. for
",alpha[2])),side=2,line=2,
>> cex.main=1.5)
>>
>> screen(6)
>> par(mar=c(3,0,0,0))
>> # now the second set
>> n1000<-bias.alpha2$nsample==1000
>> matplot(x=bias.alpha2$lambda[n1000],y=bias.alpha2[n1000,3:5],
>>
type="l",pch=1:3,col=c(4,2,3),yaxt="n",ylim=c(-.1, .6))
>> abline(h = 0, col = "gray60")
>>
>>
>>
>>
>> screen(7)
>> par(mar=c(0,3.5,3,0))
>> # now the second set
>> n250<-SE.alpha1$nsample==250
>> matplot(x=SE.alpha1$lambda[n250],y=SE.alpha1[n250,3:5],
>>
type="l",pch=1:3,col=c(4,2,3),xaxt="n",ylim=c(0,
>> 1.1),main="nsample=250",ylab="", cex.main=1)
>> abline(h = -1, col = "gray60")
>> mtext(expression(paste("SE av. for
",alpha[1])),side=2,line=2,
>> cex.main=1)
>> mtext(expression(paste(lambda)),side=1,line=2, cex.main=1.5)
>>
>>
>> screen(8)
>> par(mar=c(0,0,3,0))
>> # now the second set
>> n1000<-SE.alpha1$nsample==1000
>> matplot(x=SE.alpha1$lambda[n1000],y=SE.alpha1[n1000,3:5],
>>
type="l",pch=1:3,col=c(4,2,3),xaxt="n",yaxt="n",ylim=c(0,
>> 1.1),main="nsample=1000",ylab="")
>> abline(h = -1, col = "gray60")
>>
>>
>>
>>
>> screen(9)
>> par(mar=c(3,3.5,0,0))
>> # now the second set
>> n250<-SE.alpha2$nsample==250
>> matplot(x=SE.alpha2$lambda[n250],y=SE.alpha2[n250,3:5],
>> type="l",pch=1:3,col=c(4,2,3),ylim=c(0,
1.1),ylab="")
>> abline(h = -.5, col = "gray60")
>> mtext(expression(paste("SE av. for
",alpha[2])),side=2,line=2,
>> cex.main=1.5)
>> mtext(expression(paste(lambda)),side=1,line=2, cex.main=1.5)
>>
>>
>> screen(10)
>> par(mar=c(3,0,0,0))
>> # now the second set
>> n1000<-SE.alpha2$nsample==1000
>> matplot(x=SE.alpha2$lambda[n1000],y=SE.alpha2[n1000,3:5],
>>
type="l",pch=1:3,col=c(4,2,3),yaxt="n",ylim=c(0, 1.1))
>> abline(h = -.5, col = "gray60")
>> mtext(expression(paste(lambda)),side=1,line=2, , cex.main=1.5)
>>
>>
>>
>> screen(2)
>> par(mar=c(0,0,0,0))
>> # plot an empty plot to get the coordinates
>> plot(0:1,0:1,type="n",axes=FALSE)
>> legend(0,0.6,c("OLS", "GLS", "Reg. Cal.",
"0"),bty = "n",
>> lty=1:3,col=c(4,2,3,"gray60"),xpd=TRUE)
>>
>>
>> close.screen(all=TRUE)
>>
>>
>>
>>
>> Best,
>> RO
>>
>>
>> Atenciosamente,
>> Rosa Oliveira
>>
>> --
>>
>>
____________________________________________________________________________
>>
>>
>> Rosa Celeste dos Santos Oliveira,
>>
>> E-mail: rosita21 at gmail.com
>> Tlm: +351 939355143
>> Linkedin: https://pt.linkedin.com/in/rosacsoliveira
>>
>>
____________________________________________________________________________
>> "Many admire, few know"
>> Hippocrates
>>
>> ______________________________________________
>> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide
>> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>
>
>
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Hi Rosa, I don't think the problem is with the split.screen command, for you are getting the eight plots and the screen at the right as you requested. It looks like your margins for each plot need adjusting, and I also think you should have about a 2.2 to 1 width to height ratio in the graphics device. I can't analyze the rest of the code at the moment, but perhaps tomorrow if you can't work it out I can provide some suggestions. Jim On Fri, Sep 18, 2015 at 1:16 AM, Rosa Oliveira <rosita21 at gmail.com> wrote:> Dear Jim, > > It works, nonetheless, it doesn't slip the screen correctly :( > > Do you have any idea? > > > I used the code: > > > #setwd("/Users/RO/Dropbox/LMER - 3rdproblem/R/latest_version/graphs/data") > setwd("~/Dropbox/LMER - 3rdproblem/R/latest_version/graphs/data") > > > library(ggplot2) > library(reshape) > library(lattice) > > > # read in what looks like half of the data > > bias.alpha2<-read.csv("graphs_bias_alpha2.csv") > SE.alpha2<-read.csv("graphs_SE_alpha2.csv") > bias.alpha1<-read.csv("graphs_bias_alpha1.csv") > SE.alpha1<-read.csv("graphs_SE_alpha1.csv") > > > > quartz(width=10,height=6) > > # do the first split, to get the rightmost screen for the legend > split.screen(figs=matrix(c(0,0.84,0,1,0.84,1,0,1),nrow=2,byrow=TRUE)) > # now split the first screen to get your eight screens (numbered 3 to 10) > for the plots > split.screen(figs=matrix(c(0,0.25,0.5,1, > 0.25,0.5,0.5,1, > 0.5,0.75,0.5,1, > 0.75,1,0.5,1, > 0,0.25,0,0.5, > 0.25,0.5,0,0.5, > 0.5,0.75,0,0.5, > 0.75,1,0,0.5), > ncol=4,byrow=TRUE),screen=1) > > > > #split.screen(figs=matrix(c(0,0.5,0.5,1,#primeira linha primeira coluna > # 0.5,1,0.5,1,#primeira linha segunda coluna > # 0,0.5,0,0.5,#segunda linha primeira coluna > # 0.5,1,0,0.5),#segunda linha segunda coluna > # ncol=4,byrow=TRUE),screen=1) > > > # this produces seven screens numbered like this: > # 3 4 5 6 > # 2 > # 7 8 9 10 > # select the upper left screen > > > > screen(3) > par(mar=c(0,3.5,3,0)) > # now the second set > n250<-bias.alpha1$nsample==250 > matplot(x=bias.alpha1$lambda[n250],y=bias.alpha1[n250,3:5], > type="l",pch=1:3,col=c(4,2,3),xaxt="n",ylim=c(-.1, > .6),main="nsample=250",ylab="", cex.main=1) > abline(h = 0, col = "gray60") > mtext(expression(paste("Bias av. for ",alpha[1])),side=2,line=2, > cex.main=1) > > screen(4) > par(mar=c(0,0,3,0)) > # now the second set > n1000<-bias.alpha1$nsample==1000 > matplot(x=bias.alpha1$lambda[n1000],y=bias.alpha1[n1000,3:5], > type="l",pch=1:3,col=c(4,2,3),xaxt="n",yaxt="n",ylim=c(-.1, > .6),main="nsample=1000",ylab="") > abline(h = 0, col = "gray60") > > > > screen(5) > par(mar=c(0,3.5,3,0)) > # now the second set > par(mar=c(3,3.5,0,0)) > # now the second set > n250<-bias.alpha2$nsample==250 > matplot(x=bias.alpha2$lambda[n250],y=bias.alpha2[n250,3:5], > type="l",pch=1:3,col=c(4,2,3),ylim=c(-.1, .6),ylab="") > abline(h = 0, col = "gray60") > mtext(expression(paste("Bias av. for ",alpha[2])),side=2,line=2, > cex.main=1.5) > > screen(6) > par(mar=c(3,0,0,0)) > # now the second set > n1000<-bias.alpha2$nsample==1000 > matplot(x=bias.alpha2$lambda[n1000],y=bias.alpha2[n1000,3:5], > type="l",pch=1:3,col=c(4,2,3),yaxt="n",ylim=c(-.1, .6)) > abline(h = 0, col = "gray60") > > > > > screen(7) > par(mar=c(0,3.5,3,0)) > # now the second set > n250<-SE.alpha1$nsample==250 > matplot(x=SE.alpha1$lambda[n250],y=SE.alpha1[n250,3:5], > type="l",pch=1:3,col=c(4,2,3),xaxt="n",ylim=c(0, > 1.1),main="nsample=250",ylab="", cex.main=1) > abline(h = -1, col = "gray60") > mtext(expression(paste("SE av. for ",alpha[1])),side=2,line=2, cex.main=1) > mtext(expression(paste(lambda)),side=1,line=2, cex.main=1.5) > > > screen(8) > par(mar=c(0,0,3,0)) > # now the second set > n1000<-SE.alpha1$nsample==1000 > matplot(x=SE.alpha1$lambda[n1000],y=SE.alpha1[n1000,3:5], > type="l",pch=1:3,col=c(4,2,3),xaxt="n",yaxt="n",ylim=c(0, > 1.1),main="nsample=1000",ylab="") > abline(h = -1, col = "gray60") > > > > > screen(9) > par(mar=c(3,3.5,0,0)) > # now the second set > n250<-SE.alpha2$nsample==250 > matplot(x=SE.alpha2$lambda[n250],y=SE.alpha2[n250,3:5], > type="l",pch=1:3,col=c(4,2,3),ylim=c(0, 1.1),ylab="") > abline(h = -.5, col = "gray60") > mtext(expression(paste("SE av. for ",alpha[2])),side=2,line=2, > cex.main=1.5) > mtext(expression(paste(lambda)),side=1,line=2, cex.main=1.5) > > > screen(10) > par(mar=c(3,0,0,0)) > # now the second set > n1000<-SE.alpha2$nsample==1000 > matplot(x=SE.alpha2$lambda[n1000],y=SE.alpha2[n1000,3:5], > type="l",pch=1:3,col=c(4,2,3),yaxt="n",ylim=c(0, 1.1)) > abline(h = -.5, col = "gray60") > mtext(expression(paste(lambda)),side=1,line=2, , cex.main=1.5) > > > > screen(2) > par(mar=c(0,0,0,0)) > # plot an empty plot to get the coordinates > plot(0:1,0:1,type="n",axes=FALSE) > legend(0,0.6,c("OLS", "GLS", "Reg. Cal.", "0"),bty = "n", > lty=1:3,col=c(4,2,3,"gray60"),xpd=TRUE) > > > close.screen(all=TRUE) > > > and I attach the output graph. > > > > Best, > RO > > Atenciosamente, > Rosa Oliveira > > _________________________________ > > Antes de imprimir este e-mail pense bem se tem mesmo que o fazer. > H? cada vez menos ?rvores. > N?o imprima, pense na sua responsabilidade e compromisso com o MEIO > AMBIENTE! > > <http://pt.dreamstime.com/cora-ccedil-atildeo-criado-das-folhas-de-aacutervores-diferentes-thumb12275776.jpg> > > <http://pt.dreamstime.com/cora-ccedil-atildeo-criado-das-folhas-de-aacutervores-diferentes-thumb12275776.jpg> > > 2015-09-17 12:18 GMT+01:00 Jim Lemon <drjimlemon at gmail.com>: > >> Hi Rosa, >> Try this: >> >> # do the first split, to get the rightmost screen for the legend >> split.screen(figs=matrix(c(0,0.84,0,1,0.84,1,0,1),nrow=2,byrow=TRUE)) >> # now split the first screen to get your eight screens (numbered 3 to 10) >> for the plots >> split.screen(figs=matrix(c(0,0.25,0.5,1, >> 0.25,0.5,0.5,1, >> 0.5,0.75,0.5,1, >> 0.75,1,0.5,1, >> 0,0.25,0,0.5, >> 0.25,0.5,0,0.5, >> 0.5,0.75,0,0.5, >> 0.75,1,0,0.5), >> ncol=4,byrow=TRUE),screen=1) >> >> Jim >> >> >> On Thu, Sep 17, 2015 at 2:45 AM, Rosa Oliveira <rosita21 at gmail.com> >> wrote: >> >>> Dear all, >>> >>> I?m trying to do a graph, >>> >>> 3 rows, 5 columns, with the design: >>> # 3 4 5 6 >>> # 2 >>> # 7 8 9 10 >>> >>> I had a code for 3 rows, 3 columns, with the design:: >>> # 3 4 >>> # 2 >>> # 7 8 >>> and I tried to modify it, but I had no success :( >>> >>> I suppose the problem is in the slip.screen code (red part of the code). >>> >>> I attach my code, can anyone please help me? >>> >>> >>> Best, >>> RO >>> >>> >>> setwd("/Users/RO/Dropbox/LMER - 3rdproblem/R/latest_version/graphs/data") >>> >>> library(ggplot2) >>> library(reshape) >>> library(lattice) >>> >>> >>> # read in what looks like half of the data >>> >>> bias.alpha2<-read.csv("graphs_bias_alpha2.csv") >>> SE.alpha2<-read.csv("graphs_SE_alpha2.csv") >>> bias.alpha1<-read.csv("graphs_bias_alpha1.csv") >>> SE.alpha1<-read.csv("graphs_SE_alpha1.csv") >>> >>> >>> >>> quartz(width=10,height=6) >>> # do the first split, to get the rightmost screen for the legend >>> split.screen(figs=matrix(c(0,0.8,0,1,0.8,1,0,1),nrow=2,byrow=TRUE)) >>> # now split the first screen to get your six screens for the plots >>> >>> >>> >>> split.screen(figs=matrix(c(0,0.5,0.5,1,#primeira linha primeira coluna >>> 0.5,1,0.5,1,#primeira linha segunda coluna >>> 0,0.5,0,0.5,#segunda linha primeira coluna >>> 0.5,1,0,0.5),#segunda linha segunda coluna >>> ncol=4,byrow=TRUE),screen=1) >>> >>> >>> # this produces seven screens numbered like this: >>> # 3 4 5 6 >>> # 2 >>> # 7 8 9 10 >>> # select the upper left screen >>> >>> >>> >>> screen(3) >>> par(mar=c(0,3.5,3,0)) >>> # now the second set >>> n250<-bias.alpha1$nsample==250 >>> matplot(x=bias.alpha1$lambda[n250],y=bias.alpha1[n250,3:5], >>> type="l",pch=1:3,col=c(4,2,3),xaxt="n",ylim=c(-.1, >>> .6),main="nsample=250",ylab="", cex.main=1) >>> abline(h = 0, col = "gray60") >>> mtext(expression(paste("Bias av. for ",alpha[1])),side=2,line=2, >>> cex.main=1) >>> >>> screen(4) >>> par(mar=c(0,0,3,0)) >>> # now the second set >>> n1000<-bias.alpha1$nsample==1000 >>> matplot(x=bias.alpha1$lambda[n1000],y=bias.alpha1[n1000,3:5], >>> type="l",pch=1:3,col=c(4,2,3),xaxt="n",yaxt="n",ylim=c(-.1, >>> .6),main="nsample=1000",ylab="") >>> abline(h = 0, col = "gray60") >>> >>> >>> >>> screen(5) >>> par(mar=c(0,3.5,3,0)) >>> # now the second set >>> par(mar=c(3,3.5,0,0)) >>> # now the second set >>> n250<-bias.alpha2$nsample==250 >>> matplot(x=bias.alpha2$lambda[n250],y=bias.alpha2[n250,3:5], >>> type="l",pch=1:3,col=c(4,2,3),ylim=c(-.1, .6),ylab="") >>> abline(h = 0, col = "gray60") >>> mtext(expression(paste("Bias av. for ",alpha[2])),side=2,line=2, >>> cex.main=1.5) >>> >>> screen(6) >>> par(mar=c(3,0,0,0)) >>> # now the second set >>> n1000<-bias.alpha2$nsample==1000 >>> matplot(x=bias.alpha2$lambda[n1000],y=bias.alpha2[n1000,3:5], >>> type="l",pch=1:3,col=c(4,2,3),yaxt="n",ylim=c(-.1, .6)) >>> abline(h = 0, col = "gray60") >>> >>> >>> >>> >>> screen(7) >>> par(mar=c(0,3.5,3,0)) >>> # now the second set >>> n250<-SE.alpha1$nsample==250 >>> matplot(x=SE.alpha1$lambda[n250],y=SE.alpha1[n250,3:5], >>> type="l",pch=1:3,col=c(4,2,3),xaxt="n",ylim=c(0, >>> 1.1),main="nsample=250",ylab="", cex.main=1) >>> abline(h = -1, col = "gray60") >>> mtext(expression(paste("SE av. for ",alpha[1])),side=2,line=2, >>> cex.main=1) >>> mtext(expression(paste(lambda)),side=1,line=2, cex.main=1.5) >>> >>> >>> screen(8) >>> par(mar=c(0,0,3,0)) >>> # now the second set >>> n1000<-SE.alpha1$nsample==1000 >>> matplot(x=SE.alpha1$lambda[n1000],y=SE.alpha1[n1000,3:5], >>> type="l",pch=1:3,col=c(4,2,3),xaxt="n",yaxt="n",ylim=c(0, >>> 1.1),main="nsample=1000",ylab="") >>> abline(h = -1, col = "gray60") >>> >>> >>> >>> >>> screen(9) >>> par(mar=c(3,3.5,0,0)) >>> # now the second set >>> n250<-SE.alpha2$nsample==250 >>> matplot(x=SE.alpha2$lambda[n250],y=SE.alpha2[n250,3:5], >>> type="l",pch=1:3,col=c(4,2,3),ylim=c(0, 1.1),ylab="") >>> abline(h = -.5, col = "gray60") >>> mtext(expression(paste("SE av. for ",alpha[2])),side=2,line=2, >>> cex.main=1.5) >>> mtext(expression(paste(lambda)),side=1,line=2, cex.main=1.5) >>> >>> >>> screen(10) >>> par(mar=c(3,0,0,0)) >>> # now the second set >>> n1000<-SE.alpha2$nsample==1000 >>> matplot(x=SE.alpha2$lambda[n1000],y=SE.alpha2[n1000,3:5], >>> type="l",pch=1:3,col=c(4,2,3),yaxt="n",ylim=c(0, 1.1)) >>> abline(h = -.5, col = "gray60") >>> mtext(expression(paste(lambda)),side=1,line=2, , cex.main=1.5) >>> >>> >>> >>> screen(2) >>> par(mar=c(0,0,0,0)) >>> # plot an empty plot to get the coordinates >>> plot(0:1,0:1,type="n",axes=FALSE) >>> legend(0,0.6,c("OLS", "GLS", "Reg. Cal.", "0"),bty = "n", >>> lty=1:3,col=c(4,2,3,"gray60"),xpd=TRUE) >>> >>> >>> close.screen(all=TRUE) >>> >>> >>> >>> >>> Best, >>> RO >>> >>> >>> Atenciosamente, >>> Rosa Oliveira >>> >>> -- >>> >>> ____________________________________________________________________________ >>> >>> >>> Rosa Celeste dos Santos Oliveira, >>> >>> E-mail: rosita21 at gmail.com >>> Tlm: +351 939355143 >>> Linkedin: https://pt.linkedin.com/in/rosacsoliveira >>> >>> ____________________________________________________________________________ >>> "Many admire, few know" >>> Hippocrates >>> >>> ______________________________________________ >>> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see >>> https://stat.ethz.ch/mailman/listinfo/r-help >>> PLEASE do read the posting guide >>> http://www.R-project.org/posting-guide.html >>> and provide commented, minimal, self-contained, reproducible code. >> >> >> >[[alternative HTML version deleted]]
Hi Rosa,
I have had a moment to look at your code. First I think you should start
your device as:
quartz(width=12,height=5)
The split.screen code that I sent seems to work for me, giving the
3 4 5 6
2
7 8 9 10
layout of screens. To get the aspect ratio of the plots more similar, try
this:
# do the first split, to get the rightmost screen for the legend
split.screen(figs=matrix(c(0,0.84,0,1,0.84,1,0,1),nrow=2,byrow=TRUE))
# now split the first screen to get your eight screens (numbered 3 to 10)
for the plots
split.screen(figs=matrix(c(0,0.31,0.5,1,
0.31,0.54,0.5,1,
0.54,0.77,0.5,1,
0.77,1,0.5,1,
0,0.31,0,0.5,
0.31,0.54,0,0.5,
0.54,0.77,0,0.5,
0.77,1,0,0.5),
ncol=4,byrow=TRUE),screen=1)
I'm not sure of which plots should go on the top line and which on the
bottom, but I think you want margins like this:
screen(3)
par(mar=c(0,3.5,3,0))
screen(4)
par(mar=c(0,0,3,0))
screen(5)
par(mar=c(0,0,3,0))
screen(6)
par(mar=c(0,0,3,0))
screen(7)
par(mar=c(3,3.5,0,0))
screen(8)
par(mar=c(3,0,3,0))
screen(9)
par(mar=c(3,0,3,0))
screen(10)
par(mar=c(3,0,3,0))
Perhaps this will help.
Jim
On Fri, Sep 18, 2015 at 6:14 AM, Jim Lemon <drjimlemon at gmail.com>
wrote:
> Hi Rosa,
> I don't think the problem is with the split.screen command, for you are
> getting the eight plots and the screen at the right as you requested. It
> looks like your margins for each plot need adjusting, and I also think you
> should have about a 2.2 to 1 width to height ratio in the graphics device.
> I can't analyze the rest of the code at the moment, but perhaps
tomorrow if
> you can't work it out I can provide some suggestions.
>
> Jim
>
>
> On Fri, Sep 18, 2015 at 1:16 AM, Rosa Oliveira <rosita21 at
gmail.com> wrote:
>
>> Dear Jim,
>>
>> It works, nonetheless, it doesn't slip the screen correctly :(
>>
>> Do you have any idea?
>>
>>
>> I used the code:
>>
>>
>> #setwd("/Users/RO/Dropbox/LMER -
3rdproblem/R/latest_version/graphs/data")
>> setwd("~/Dropbox/LMER -
3rdproblem/R/latest_version/graphs/data")
>>
>>
>> library(ggplot2)
>> library(reshape)
>> library(lattice)
>>
>>
>> # read in what looks like half of the data
>>
>> bias.alpha2<-read.csv("graphs_bias_alpha2.csv")
>> SE.alpha2<-read.csv("graphs_SE_alpha2.csv")
>> bias.alpha1<-read.csv("graphs_bias_alpha1.csv")
>> SE.alpha1<-read.csv("graphs_SE_alpha1.csv")
>>
>>
>>
>> quartz(width=10,height=6)
>>
>> # do the first split, to get the rightmost screen for the legend
>> split.screen(figs=matrix(c(0,0.84,0,1,0.84,1,0,1),nrow=2,byrow=TRUE))
>> # now split the first screen to get your eight screens (numbered 3 to
10)
>> for the plots
>> split.screen(figs=matrix(c(0,0.25,0.5,1,
>> 0.25,0.5,0.5,1,
>> 0.5,0.75,0.5,1,
>> 0.75,1,0.5,1,
>> 0,0.25,0,0.5,
>> 0.25,0.5,0,0.5,
>> 0.5,0.75,0,0.5,
>> 0.75,1,0,0.5),
>> ncol=4,byrow=TRUE),screen=1)
>>
>>
>>
>> #split.screen(figs=matrix(c(0,0.5,0.5,1,#primeira linha primeira coluna
>> # 0.5,1,0.5,1,#primeira linha segunda coluna
>> # 0,0.5,0,0.5,#segunda linha primeira coluna
>> # 0.5,1,0,0.5),#segunda linha segunda coluna
>> # ncol=4,byrow=TRUE),screen=1)
>>
>>
>> # this produces seven screens numbered like this:
>> # 3 4 5 6
>> # 2
>> # 7 8 9 10
>> # select the upper left screen
>>
>>
>>
>> screen(3)
>> par(mar=c(0,3.5,3,0))
>> # now the second set
>> n250<-bias.alpha1$nsample==250
>> matplot(x=bias.alpha1$lambda[n250],y=bias.alpha1[n250,3:5],
>>
type="l",pch=1:3,col=c(4,2,3),xaxt="n",ylim=c(-.1,
>> .6),main="nsample=250",ylab="", cex.main=1)
>> abline(h = 0, col = "gray60")
>> mtext(expression(paste("Bias av. for
",alpha[1])),side=2,line=2,
>> cex.main=1)
>>
>> screen(4)
>> par(mar=c(0,0,3,0))
>> # now the second set
>> n1000<-bias.alpha1$nsample==1000
>> matplot(x=bias.alpha1$lambda[n1000],y=bias.alpha1[n1000,3:5],
>>
type="l",pch=1:3,col=c(4,2,3),xaxt="n",yaxt="n",ylim=c(-.1,
>> .6),main="nsample=1000",ylab="")
>> abline(h = 0, col = "gray60")
>>
>>
>>
>> screen(5)
>> par(mar=c(0,3.5,3,0))
>> # now the second set
>> par(mar=c(3,3.5,0,0))
>> # now the second set
>> n250<-bias.alpha2$nsample==250
>> matplot(x=bias.alpha2$lambda[n250],y=bias.alpha2[n250,3:5],
>> type="l",pch=1:3,col=c(4,2,3),ylim=c(-.1,
.6),ylab="")
>> abline(h = 0, col = "gray60")
>> mtext(expression(paste("Bias av. for
",alpha[2])),side=2,line=2,
>> cex.main=1.5)
>>
>> screen(6)
>> par(mar=c(3,0,0,0))
>> # now the second set
>> n1000<-bias.alpha2$nsample==1000
>> matplot(x=bias.alpha2$lambda[n1000],y=bias.alpha2[n1000,3:5],
>>
type="l",pch=1:3,col=c(4,2,3),yaxt="n",ylim=c(-.1, .6))
>> abline(h = 0, col = "gray60")
>>
>>
>>
>>
>> screen(7)
>> par(mar=c(0,3.5,3,0))
>> # now the second set
>> n250<-SE.alpha1$nsample==250
>> matplot(x=SE.alpha1$lambda[n250],y=SE.alpha1[n250,3:5],
>>
type="l",pch=1:3,col=c(4,2,3),xaxt="n",ylim=c(0,
>> 1.1),main="nsample=250",ylab="", cex.main=1)
>> abline(h = -1, col = "gray60")
>> mtext(expression(paste("SE av. for
",alpha[1])),side=2,line=2,
>> cex.main=1)
>> mtext(expression(paste(lambda)),side=1,line=2, cex.main=1.5)
>>
>>
>> screen(8)
>> par(mar=c(0,0,3,0))
>> # now the second set
>> n1000<-SE.alpha1$nsample==1000
>> matplot(x=SE.alpha1$lambda[n1000],y=SE.alpha1[n1000,3:5],
>>
type="l",pch=1:3,col=c(4,2,3),xaxt="n",yaxt="n",ylim=c(0,
>> 1.1),main="nsample=1000",ylab="")
>> abline(h = -1, col = "gray60")
>>
>>
>>
>>
>> screen(9)
>> par(mar=c(3,3.5,0,0))
>> # now the second set
>> n250<-SE.alpha2$nsample==250
>> matplot(x=SE.alpha2$lambda[n250],y=SE.alpha2[n250,3:5],
>> type="l",pch=1:3,col=c(4,2,3),ylim=c(0,
1.1),ylab="")
>> abline(h = -.5, col = "gray60")
>> mtext(expression(paste("SE av. for
",alpha[2])),side=2,line=2,
>> cex.main=1.5)
>> mtext(expression(paste(lambda)),side=1,line=2, cex.main=1.5)
>>
>>
>> screen(10)
>> par(mar=c(3,0,0,0))
>> # now the second set
>> n1000<-SE.alpha2$nsample==1000
>> matplot(x=SE.alpha2$lambda[n1000],y=SE.alpha2[n1000,3:5],
>>
type="l",pch=1:3,col=c(4,2,3),yaxt="n",ylim=c(0, 1.1))
>> abline(h = -.5, col = "gray60")
>> mtext(expression(paste(lambda)),side=1,line=2, , cex.main=1.5)
>>
>>
>>
>> screen(2)
>> par(mar=c(0,0,0,0))
>> # plot an empty plot to get the coordinates
>> plot(0:1,0:1,type="n",axes=FALSE)
>> legend(0,0.6,c("OLS", "GLS", "Reg. Cal.",
"0"),bty = "n",
>> lty=1:3,col=c(4,2,3,"gray60"),xpd=TRUE)
>>
>>
>> close.screen(all=TRUE)
>>
>>
>> and I attach the output graph.
>>
>>
>>
>> Best,
>> RO
>>
>> Atenciosamente,
>> Rosa Oliveira
>>
>> _________________________________
>>
>> Antes de imprimir este e-mail pense bem se tem mesmo que o fazer.
>> H? cada vez menos ?rvores.
>> N?o imprima, pense na sua responsabilidade e compromisso com o MEIO
>> AMBIENTE!
>>
>>
<http://pt.dreamstime.com/cora-ccedil-atildeo-criado-das-folhas-de-aacutervores-diferentes-thumb12275776.jpg>
>>
>>
<http://pt.dreamstime.com/cora-ccedil-atildeo-criado-das-folhas-de-aacutervores-diferentes-thumb12275776.jpg>
>>
>> 2015-09-17 12:18 GMT+01:00 Jim Lemon <drjimlemon at gmail.com>:
>>
>>> Hi Rosa,
>>> Try this:
>>>
>>> # do the first split, to get the rightmost screen for the legend
>>>
split.screen(figs=matrix(c(0,0.84,0,1,0.84,1,0,1),nrow=2,byrow=TRUE))
>>> # now split the first screen to get your eight screens (numbered 3
to
>>> 10) for the plots
>>> split.screen(figs=matrix(c(0,0.25,0.5,1,
>>> 0.25,0.5,0.5,1,
>>> 0.5,0.75,0.5,1,
>>> 0.75,1,0.5,1,
>>> 0,0.25,0,0.5,
>>> 0.25,0.5,0,0.5,
>>> 0.5,0.75,0,0.5,
>>> 0.75,1,0,0.5),
>>> ncol=4,byrow=TRUE),screen=1)
>>>
>>> Jim
>>>
>>>
>>> On Thu, Sep 17, 2015 at 2:45 AM, Rosa Oliveira <rosita21 at
gmail.com>
>>> wrote:
>>>
>>>> Dear all,
>>>>
>>>> I?m trying to do a graph,
>>>>
>>>> 3 rows, 5 columns, with the design:
>>>> # 3 4 5 6
>>>> # 2
>>>> # 7 8 9 10
>>>>
>>>> I had a code for 3 rows, 3 columns, with the design::
>>>> # 3 4
>>>> # 2
>>>> # 7 8
>>>> and I tried to modify it, but I had no success :(
>>>>
>>>> I suppose the problem is in the slip.screen code (red part of
the code).
>>>>
>>>> I attach my code, can anyone please help me?
>>>>
>>>>
>>>> Best,
>>>> RO
>>>>
>>>>
>>>> setwd("/Users/RO/Dropbox/LMER -
>>>> 3rdproblem/R/latest_version/graphs/data")
>>>>
>>>> library(ggplot2)
>>>> library(reshape)
>>>> library(lattice)
>>>>
>>>>
>>>> # read in what looks like half of the data
>>>>
>>>> bias.alpha2<-read.csv("graphs_bias_alpha2.csv")
>>>> SE.alpha2<-read.csv("graphs_SE_alpha2.csv")
>>>> bias.alpha1<-read.csv("graphs_bias_alpha1.csv")
>>>> SE.alpha1<-read.csv("graphs_SE_alpha1.csv")
>>>>
>>>>
>>>>
>>>> quartz(width=10,height=6)
>>>> # do the first split, to get the rightmost screen for the
legend
>>>>
split.screen(figs=matrix(c(0,0.8,0,1,0.8,1,0,1),nrow=2,byrow=TRUE))
>>>> # now split the first screen to get your six screens for the
plots
>>>>
>>>>
>>>>
>>>> split.screen(figs=matrix(c(0,0.5,0.5,1,#primeira linha primeira
coluna
>>>> 0.5,1,0.5,1,#primeira linha segunda
coluna
>>>> 0,0.5,0,0.5,#segunda linha primeira
coluna
>>>> 0.5,1,0,0.5),#segunda linha segunda
coluna
>>>> ncol=4,byrow=TRUE),screen=1)
>>>>
>>>>
>>>> # this produces seven screens numbered like this:
>>>> # 3 4 5 6
>>>> # 2
>>>> # 7 8 9 10
>>>> # select the upper left screen
>>>>
>>>>
>>>>
>>>> screen(3)
>>>> par(mar=c(0,3.5,3,0))
>>>> # now the second set
>>>> n250<-bias.alpha1$nsample==250
>>>> matplot(x=bias.alpha1$lambda[n250],y=bias.alpha1[n250,3:5],
>>>>
type="l",pch=1:3,col=c(4,2,3),xaxt="n",ylim=c(-.1,
>>>> .6),main="nsample=250",ylab="", cex.main=1)
>>>> abline(h = 0, col = "gray60")
>>>> mtext(expression(paste("Bias av. for
",alpha[1])),side=2,line=2,
>>>> cex.main=1)
>>>>
>>>> screen(4)
>>>> par(mar=c(0,0,3,0))
>>>> # now the second set
>>>> n1000<-bias.alpha1$nsample==1000
>>>> matplot(x=bias.alpha1$lambda[n1000],y=bias.alpha1[n1000,3:5],
>>>>
type="l",pch=1:3,col=c(4,2,3),xaxt="n",yaxt="n",ylim=c(-.1,
>>>> .6),main="nsample=1000",ylab="")
>>>> abline(h = 0, col = "gray60")
>>>>
>>>>
>>>>
>>>> screen(5)
>>>> par(mar=c(0,3.5,3,0))
>>>> # now the second set
>>>> par(mar=c(3,3.5,0,0))
>>>> # now the second set
>>>> n250<-bias.alpha2$nsample==250
>>>> matplot(x=bias.alpha2$lambda[n250],y=bias.alpha2[n250,3:5],
>>>> type="l",pch=1:3,col=c(4,2,3),ylim=c(-.1,
.6),ylab="")
>>>> abline(h = 0, col = "gray60")
>>>> mtext(expression(paste("Bias av. for
",alpha[2])),side=2,line=2,
>>>> cex.main=1.5)
>>>>
>>>> screen(6)
>>>> par(mar=c(3,0,0,0))
>>>> # now the second set
>>>> n1000<-bias.alpha2$nsample==1000
>>>> matplot(x=bias.alpha2$lambda[n1000],y=bias.alpha2[n1000,3:5],
>>>>
type="l",pch=1:3,col=c(4,2,3),yaxt="n",ylim=c(-.1, .6))
>>>> abline(h = 0, col = "gray60")
>>>>
>>>>
>>>>
>>>>
>>>> screen(7)
>>>> par(mar=c(0,3.5,3,0))
>>>> # now the second set
>>>> n250<-SE.alpha1$nsample==250
>>>> matplot(x=SE.alpha1$lambda[n250],y=SE.alpha1[n250,3:5],
>>>>
type="l",pch=1:3,col=c(4,2,3),xaxt="n",ylim=c(0,
>>>> 1.1),main="nsample=250",ylab="",
cex.main=1)
>>>> abline(h = -1, col = "gray60")
>>>> mtext(expression(paste("SE av. for
",alpha[1])),side=2,line=2,
>>>> cex.main=1)
>>>> mtext(expression(paste(lambda)),side=1,line=2, cex.main=1.5)
>>>>
>>>>
>>>> screen(8)
>>>> par(mar=c(0,0,3,0))
>>>> # now the second set
>>>> n1000<-SE.alpha1$nsample==1000
>>>> matplot(x=SE.alpha1$lambda[n1000],y=SE.alpha1[n1000,3:5],
>>>>
type="l",pch=1:3,col=c(4,2,3),xaxt="n",yaxt="n",ylim=c(0,
>>>> 1.1),main="nsample=1000",ylab="")
>>>> abline(h = -1, col = "gray60")
>>>>
>>>>
>>>>
>>>>
>>>> screen(9)
>>>> par(mar=c(3,3.5,0,0))
>>>> # now the second set
>>>> n250<-SE.alpha2$nsample==250
>>>> matplot(x=SE.alpha2$lambda[n250],y=SE.alpha2[n250,3:5],
>>>> type="l",pch=1:3,col=c(4,2,3),ylim=c(0,
1.1),ylab="")
>>>> abline(h = -.5, col = "gray60")
>>>> mtext(expression(paste("SE av. for
",alpha[2])),side=2,line=2,
>>>> cex.main=1.5)
>>>> mtext(expression(paste(lambda)),side=1,line=2, cex.main=1.5)
>>>>
>>>>
>>>> screen(10)
>>>> par(mar=c(3,0,0,0))
>>>> # now the second set
>>>> n1000<-SE.alpha2$nsample==1000
>>>> matplot(x=SE.alpha2$lambda[n1000],y=SE.alpha2[n1000,3:5],
>>>>
type="l",pch=1:3,col=c(4,2,3),yaxt="n",ylim=c(0, 1.1))
>>>> abline(h = -.5, col = "gray60")
>>>> mtext(expression(paste(lambda)),side=1,line=2, , cex.main=1.5)
>>>>
>>>>
>>>>
>>>> screen(2)
>>>> par(mar=c(0,0,0,0))
>>>> # plot an empty plot to get the coordinates
>>>> plot(0:1,0:1,type="n",axes=FALSE)
>>>> legend(0,0.6,c("OLS", "GLS", "Reg.
Cal.", "0"),bty = "n",
>>>> lty=1:3,col=c(4,2,3,"gray60"),xpd=TRUE)
>>>>
>>>>
>>>> close.screen(all=TRUE)
>>>>
>>>>
>>>>
>>>>
>>>> Best,
>>>> RO
>>>>
>>>>
>>>> Atenciosamente,
>>>> Rosa Oliveira
>>>>
>>>> --
>>>>
>>>>
____________________________________________________________________________
>>>>
>>>>
>>>> Rosa Celeste dos Santos Oliveira,
>>>>
>>>> E-mail: rosita21 at gmail.com
>>>> Tlm: +351 939355143
>>>> Linkedin: https://pt.linkedin.com/in/rosacsoliveira
>>>>
>>>>
____________________________________________________________________________
>>>> "Many admire, few know"
>>>> Hippocrates
>>>>
>>>> ______________________________________________
>>>> R-help at r-project.org mailing list -- To UNSUBSCRIBE and
more, see
>>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>>> PLEASE do read the posting guide
>>>> http://www.R-project.org/posting-guide.html
>>>> and provide commented, minimal, self-contained, reproducible
code.
>>>
>>>
>>>
>>
>
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