(This article was first published on

**Wiekvoet**, and kindly contributed to R-bloggers)Sometimes I have the desire to plot both on the linear and on the log scale. To save space just two figures is not my solution. I want to reuse the x-axis, legend, title. This post examines possibilities to do so with standard plot tools, lattice and ggplot2.

### Data

Data is completely artificial.

library(ggplot2)

library(lattice)

datastart <- data.frame(x=rep(1:5,2),

y=c(1,2,10,50,1, .1,9,8,20,19),

type=rep(c(‘a’,’b’),each=5))

datastart

x y type

1 1 1.0 a

2 2 2.0 a

3 3 10.0 a

4 4 50.0 a

5 5 1.0 a

6 1 0.1 b

7 2 9.0 b

8 3 8.0 b

9 4 20.0 b

10 5 19.0 b

### standard plot tools

The trick here is to make two plots. The top plot has no x-axis, the bottom one no title. To make the two plot surfaces equal in size the room reserved for x-axis and title is the same.

par(mfrow=c(2,1),mar=c(0,4.1,4,2))

plot(y~x,

data=datastart,

axes=FALSE,

frame.plot=TRUE,

xlab=”,

main=’bla bla’,

col=c(‘red’,’green’)[datastart$type])

legend(x=’topleft’,

legend=c(‘a’,’b’),

col=c(‘red’,’green’),

pch=1)

axis(side=2,las=1)

par(mar=c(4,4.1,0,2))

plot(y~x,

data=datastart,

axes=FALSE,

frame.plot=TRUE,

xlab=’x’,

log=’y’,

ylab=’log(y)’,

col=c(‘red’,’green’)[datastart$type]

)

axis(side=2,las=1)

axis(side=1)

### lattice

As far as I understand, lattice does not have the tools to fiddle this extreme with axis. The trick then is to add a copy of the data on logarithmic scale and manually control the labels. Lattice does not understand that the x-axis are same, but some suppression is possible.

data1=datastart

data2=datastart

data1$lab=’linear’

data2$lab=’log’

data2$y <- log10(data2$y)

dataplot <- rbind(data1,data2)

at2 <- axisTicks(range(data2$y),log=TRUE,nint=4)

at1 <- axisTicks(range(data1$y),log=FALSE,nint=5)

atx <- axisTicks(range(data1$x),log=FALSE,nint=5)

dataplot$lab <- factor(dataplot$lab,levels=c(‘linear’,’log’))

xyplot(y ~ x | lab,groups=type,data=dataplot,layout=c(1,2),

main=’bla bla’,

as.table=TRUE,

auto.key=TRUE,

scales=list(relation=’free’,

x=list(at=list(NULL,atx)),

y=list(at=list(at1,log10(at2)),

labels=list(format(at1),format(at2))

)

))

### ggplot2

The trick here is that ggplot2 can have a free y-axis, but you cannot set the labels per axis. Instead it is a common y-axis which has adapted labels. ggplot chooses the range for the y-axis itself, you have to make sure that the labels you feed it match that range. To make that fit in the end I just shifted the whole log part to a different range. Some of the code of lattice is re-used.

dataplot2 <- dataplot

offset <- -10

breaks=c(-11,-10,-9)

dataplot2$y[dataplot2$lab==’log’] <- dataplot2$y[dataplot2$lab==’log’] +offset

p <- ggplot(dataplot2, aes(x, y,colour=type)) + geom_point()

p + facet_grid(lab ~ .,

scales=’free_y’) +

labs(title = ‘bla bla’) +

scale_y_continuous(

breaks = c(breaks,at1),

labels=c(format(10^(breaks-offset)),format(at1)))

To

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