Specifying Complex Plot Arrangements
Description
layout
divides the device up into as many rows and columns as
there are in matrix mat
, with the columnwidths and the
rowheights specified in the respective arguments.
Usage
1 2 3 4 5 
Arguments
mat 
a matrix object specifying the location of the next
N figures on the output device. Each value in the matrix must
be 
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 
heights 
a vector of values for the heights of rows on the device.
Relative and absolute heights can be specified, see 
respect 
either a logical value or a matrix object. If the
latter, then it must have the same dimensions as 
n 
number of figures to plot. 
x 
a dimension to be interpreted as a number of centimetres. 
Details
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 columnwidth is
the same physical measurement on the device as a unit rowheight.
There is a limit (currently 200) for the numbers of rows and columns in the layout, and also for the total number of cells (10007).
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()
.
Value
layout
returns the number of figures, N, see above.
Warnings
These functions are totally incompatible with the other mechanisms for
arranging plots on a device: par(mfrow)
,
par(mfcol)
and split.screen
.
Author(s)
Paul R. Murrell
References
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.
Murrell, P. (2005) R Graphics. Chapman & Hall/CRC Press.
See Also
par
with arguments mfrow
, mfcol
, or
mfg
.
Examples
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40  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, stats::rnorm(50)))
y < pmin(3, pmax(3, stats::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
