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 <rosit...@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: rosit...@gmail.com
> Tlm: +351 939355143
> Linkedin: https://pt.linkedin.com/in/rosacsoliveira
>
> ____________________________________________________________________________
> "Many admire, few know"
> Hippocrates
>
> ______________________________________________
> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
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> 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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