layout {base} | R Documentation

## Specifying Complex Plot Arrangements

### Description

`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.

### Usage

    layout(mat,
           widths = rep(1, dim(mat)[2]),
           heights= rep(1, dim(mat)[1]),
           respect= FALSE)

    layout.show(n = 1)
    lcm(x)

### Arguments

`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`.

### 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 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()`.

### Value

`layout` returns the number of figures, N, see above.

### 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.

### See Also

`par(mfrow=..)`, `par(mfcol=..)` and `par(mfg=..)`

### Examples

     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,T), 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