layout                 package:base                 R Documentation

_S_p_e_c_i_f_y_i_n_g _C_o_m_p_l_e_x _P_l_o_t _A_r_r_a_n_g_e_m_e_n_t_s

_D_e_s_c_r_i_p_t_i_o_n:

     `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.

_U_s_a_g_e:

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

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

_A_r_g_u_m_e_n_t_s:

     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'.

_D_e_t_a_i_l_s:

     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()'.

_V_a_l_u_e:

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

_A_u_t_h_o_r(_s):

     Paul R. Murrell

_R_e_f_e_r_e_n_c_e_s:

     Chapter 5 of Paul Murrell's Ph.D. thesis.

_S_e_e _A_l_s_o:

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

_E_x_a_m_p_l_e_s:

      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=T))
      ## 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=T), respect=T)
      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 <- rnorm(50)
      y <- rnorm(50)
      xhist <- hist(x, breaks=seq(-3,3,0.5), plot=F)
      yhist <- hist(y, breaks=seq(-3,3,0.5), plot=F)
      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), T)
      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$counts, axes=F, ylim=c(0, top), space=0)
      par(mar=c(3,0,1,1))
      barplot(yhist$counts, axes=F, xlim=c(0, top), space=0, horiz=T)

      par(def.par)#- reset to default

