Specifying Complex Plot Arrangements

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.

dplot, environment, iplot
layout(mat, widths =, ncol(mat)), heights =, nrow(mat)), respect = FALSE) = 1) lcm(x)
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 ${1, \dots, N-1}$ must also appear at least once in the matrix.
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).
a vector of values for the heights of rows on the device. Relative and absolute heights can be specified, see widths above.
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.
number of figures to plot.
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.
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). 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.


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.

  • layout
  • lcm
library(graphics) 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 ## 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) ## create single figure which is 5cm square nf <- layout(matrix(1), widths = lcm(5), heights = lcm(5)) ##-- 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) 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
Documentation reproduced from package graphics, version 3.0.3, License: Part of R 3.0.3

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