image.plot: Draws image plot with a legend strip for the color scale.

Description

This function combines the R image function with some automatic placement of a legend. This is done by splitting the plotting region into two parts. Putting the image in one and the legend in the other.

Usage

image.plot(..., add = FALSE, nlevel = 64, legend.shrink = 0.9,
                 legend.width = 0.05, graphics.reset = FALSE,
                 horizontal = FALSE, offset = 2 * legend.width,
                 bigplot = NULL, smallplot = NULL, legend.only =
                 FALSE, col = tim.colors(nlevel))

Arguments

Side Effects

After exiting, the plotting region may be changed to make it possible to add more features to the plot. To be explicit, par()$plt may be changed to reflect a smaller plotting region that has accommodated room for the legend subplot.

Details

If the z component is a matrix then the user should know that this function locates the matrix element z[i,j] at the grid locations (x[i], y[j]) this is very diiffernet than simply listing out the matrix in the usual row column tabular form. See the example below for more details of this difference in formatting.

It is surprising how hard it is just to automatically add the legend! All "plotting coordinates" mentioned here are in device coordinates. The plot region is assumed to be [0,1]X[0,1] and plotting regions are defined as rectangles within this square. We found these easier to work with than user coordinates. There are always problems with default solutions to placing information on graphs but the choices made here may be useful for most cases. The most annoying thing is that after using plot.image and adding information the next plot that is made may have the slightly smaller plotting region set by the image plotting. The user should set reset.graphics=TRUE to avoid the plotting size some from changing. The disadvantage, however, of resetting the graphics is that one can no longer add additional graphics elements to the image plot. (Note that filled.contour always resets the graphics but provides another mechanism to pass through plotting commands. Apparently filled.contour,while very pretty, does not work for multiple plots ... )

The strategy for image.plot is simple, divide the plotting region into two smaller regions bigplot and smallplot. The image goes in one and the legend in the other. This way there is always room for the legend. Some adjustments are made to this rule by not shrinking the bigplot if there is already room for the legend strip and also sticking the legend strip close to the image plot. One can specify the plot regions explicitly by bigplot and smallplot if the default choices do not work. There may be problems with small plotting regions in fitting both of these in the plot region and one may have to change the default character sizes or margins to make things fit.

By keeping the zlim argument the same across images one can generate the same color scale. (See the image help file) One useful technique for a panel of images is to just draw the first with image.plot to get a legend and just use image for subsequent plots. Also keep in mind one can just add a legend to an existing plot without changing plotting parameters. Usually a square plot (pty="s") done in a rectangular plot region will have room for the legend with any adjustments stuck to the right side.

Note that to add just the legend strip all one needs is the zlim argument! The default color table for this function is the topographic color scale (topo.colors) showing our geophysical basis. See also terrain.colors for a subset. For using other color choices see how the nlevels argument figures into the legend and main plot number of colors. We like tim.colors as a defualt color scale.

Examples

Run this code

x<- 1:10 
y<- 1:15 
z<- outer( x,y,"+") 
image.plot(x,y,z) 

# or obj<- list( x=x,y=y,z=z); image.plot(obj)

# now add some points on diagonal with some clipping anticipated 
   points( 5:12, 5:12, pch="X", cex=3)

#
#fat (5\% of figure) and short (50\% of figure)  legend strip on the bottom 
  image.plot( x,y,z,legend.width=.05, legend.shrink=.5, horizontal=TRUE) 



set.panel()

#
# Here is a strategy to add a common legend to a panel of plots
# consult the  split.screen help file for more explanations
# draw two images top and bottom and add a single legned strip on the right side
# first divide screen into the figure region and strip on the right ot put a 
# legend. 

   split.screen( rbind(c(0, .8,0,1), c(.8,1,0,1)))

# now divide up the figure region 
   split.screen(c(2,1), screen=1)-> ind

zr<- range( 2,35)
# first image
   screen( ind[1])
   image( x,y,z, col=tim.colors(), zlim=zr)

# second image
   screen( ind[2])
   image( x,y,z+10, col=tim.colors(), zlim =zr)

# move to skinny region on right and draw the legend strip 
   screen( 2)
   image.plot( zlim=zr,legend.only=TRUE, smallplot=c(.1,.2, .3,.7),
   col=tim.colors())

   close.screen( all=TRUE)


# you can always add a legend arbitrarily to any plot;
# note that here the plot is too big for the vertical strip but the
# horizontal fits nicely.
plot( 1:10, 1:10)
image.plot( zlim=c(0,25), legend.only=TRUE)
image.plot( zlim=c(0,25), legend.only=TRUE, horizontal =TRUE)

# combining the  usual image function and adding a legend
# first change margin for some more room
par( mar=c(10,5,5,5))
image( x,y,z, col=topo.colors(64))
image.plot( zlim=c(0,25), nlevel=64,legend.only=TRUE, horizontal=TRUE)
#
# 
# sorting difference in formatting between matrix storage and the image 
#plot depiction
A<- matrix( 1:48, ncol=6)
# Note that matrix(c(A), ncol=6) == A
image.plot(1:8, 1:6, A)
# add labels to each box 
text( c( row(A)), c( col(A)), A)
# and the indices ...
text( c( row(A)), c( col(A))-.25,  
   paste( "(", c(row(A)), ",",c(col(A)),")", sep=""), col=2)

# "columns" of A are horizontal and rows are ordered from bottom to top!
#
# matrix in its usual tabluar form where the rows are y  and columns are x
image.plot( t( A[6:1,]), axes=FALSE)