| layout {graphics} | R Documentation |
layout divides the device up into as many rows and columns as
there are in matrix mat, with the column-widths and the
row-heights specified in the respective arguments.
layout(mat,
widths = rep(1, dim(mat)[2]),
heights = rep(1, dim(mat)[1]),
respect = FALSE)
layout.show(n = 1)
lcm(x)
mat |
a matrix object specifying the location of the next
N figures
on the output device. Each value in the matrix must be 0 or a
positive integer. If N is the largest positive integer in
the matrix, then the integers {1,...,N-1} must also appear
at least once in the matrix. |
widths |
a vector of values for the widths of columns on the
device. Relative widths are specified with numeric values. Absolute
widths (in centimetres) are specified with the lcm() function (see
examples). |
heights |
a vector of values for the heights of rows on the device.
Relative and absolute heights can be specified, see widths above. |
respect |
either a logical value or a matrix object. If the
latter, then it must have the same dimensions as mat and
each value in the matrix must be either 0 or 1. |
n |
number of figures to plot. |
x |
a dimension to be interpreted as a number of centimetres. |
Figure i is allocated a region composed from a subset
of these rows and columns, based on the rows and columns
in which i occurs in mat.
The respect argument controls whether a unit column-width is
the same physical measurement on the device as a unit row-height.
layout.show(n) plots (part of) the current layout, namely the
outlines of the next n figures.
lcm is a trivial function, to be used as the interface
for specifying absolute dimensions for the widths and
heights arguments of layout().
layout returns the number of figures, N, see above.
These functions are totally incompatible with the other mechanisms for
arranging plots on a device: par(mfrow),
par(mfcol) and split.screen.
Paul R. Murrell
Murrell, P. R. (1999) Layouts: A mechanism for arranging plots on a page. Journal of Computational and Graphical Statistics, 8, 121-134. Chapter 5 of Paul Murrell's Ph.D. thesis.
par with arguments mfrow, mfcol, or
mfg.
def.par <- par(no.readonly = TRUE) # save default, for resetting... ## divide the device into two rows and two columns ## allocate figure 1 all of row 1 ## allocate figure 2 the intersection of column 2 and row 2 layout(matrix(c(1,1,0,2), 2, 2, byrow = TRUE)) ## show the regions that have been allocated to each plot layout.show(2) ## divide device into two rows and two columns ## allocate figure 1 and figure 2 as above ## respect relations between widths and heights nf <- layout(matrix(c(1,1,0,2), 2, 2, byrow=TRUE), respect=TRUE) layout.show(nf) ## create single figure which is 5cm square nf <- layout(matrix(1), widths=lcm(5), heights=lcm(5)) layout.show(nf) ##-- Create a scatterplot with marginal histograms ----- x <- pmin(3, pmax(-3, rnorm(50))) y <- pmin(3, pmax(-3, rnorm(50))) xhist <- hist(x, breaks=seq(-3,3,0.5), plot=FALSE) yhist <- hist(y, breaks=seq(-3,3,0.5), plot=FALSE) top <- max(c(xhist$counts, yhist$counts)) xrange <- c(-3,3) yrange <- c(-3,3) nf <- layout(matrix(c(2,0,1,3),2,2,byrow=TRUE), c(3,1), c(1,3), TRUE) layout.show(nf) par(mar=c(3,3,1,1)) plot(x, y, xlim=xrange, ylim=yrange, xlab="", ylab="") par(mar=c(0,3,1,1)) barplot(xhist$counts, axes=FALSE, ylim=c(0, top), space=0) par(mar=c(3,0,1,1)) barplot(yhist$counts, axes=FALSE, xlim=c(0, top), space=0, horiz=TRUE) par(def.par)#- reset to default