Dear Jim,
I’ve tried till today, but I could not solve the problems.
1. despite the scales are the same (equal: lambda ={0.70, 0.75, 0.80, 0.85,
0.90, 0.95, 0.98}), the "matrix" is not equal. If you see, for n = 250 the
column is narrower than for n = 1000, and "lambda" has the same values.
2. the first 2 columns relate to alpha 1 and the second two columns alpha2. Is
it possible to place a title above nsample that concerns the first 2 columns
and other over the last 2?
something like:
alpha1
alpha2
nsample=250 nsample=1000 nsample=250 nsample=1000
3. Notice that have 4 separate drawings and must place the 4 "groups" together.
Can you help?
It's really important.
Best,
RO
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),xaxt="n",yaxt="n",ylim=c(-.1,
.6),main="nsample=250",ylab="")
abline(h = 0, col = "gray60")
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),xaxt="n",yaxt="n",ylim=c(-.1,
.6),main="nsample=1000",ylab="")
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),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),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),yaxt="n",ylim=c(0, 1.1),ylab="")
abline(h = -.5, col = "gray60")
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),ylab="")
abline(h = -1, 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)
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
> On 18 Sep 2015, at 10:38, Jim Lemon <drjimle...@gmail.com> wrote:
>
> 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 <drjimle...@gmail.com
> <mailto:drjimle...@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 <rosit...@gmail.com
> <mailto:rosit...@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!
>
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>
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>
> 2015-09-17 12:18 GMT+01:00 Jim Lemon <drjimle...@gmail.com
> <mailto:drjimle...@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 <rosit...@gmail.com
> <mailto: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 <mailto:rosit...@gmail.com>
> Tlm: +351 939355143 <tel:%2B351%20939355143>
> Linkedin: https://pt.linkedin.com/in/rosacsoliveira
> <https://pt.linkedin.com/in/rosacsoliveira>
> ____________________________________________________________________________
> "Many admire, few know"
> Hippocrates
>
> ______________________________________________
> R-help@r-project.org <mailto:R-help@r-project.org> mailing list -- To
> UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> <https://stat.ethz.ch/mailman/listinfo/r-help>
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> <http://www.r-project.org/posting-guide.html>
> and provide commented, minimal, self-contained, reproducible code.
>
>
>
>
______________________________________________
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
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