[R] HELP IN GRAPHS - slip screen
Jim Lemon
drjimlemon at gmail.com
Thu Sep 17 22:14:42 CEST 2015
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.
> Há cada vez menos árvores.
> Não 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
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>>> http://www.R-project.org/posting-guide.html
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>>
>>
>>
>
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