image.plot {fields}R Documentation

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


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.


image.plot(..., add = FALSE, nlevel = 64, legend.shrink = 0.9, 
legend.width = 1.2, legend.mar = NULL, 
graphics.reset = FALSE, horizontal = FALSE, bigplot = NULL
, smallplot = NULL, legend.only = FALSE, col = tim.colors(nlevel),
lab.breaks=NULL, axis.args=NULL)


... The usual arguments to the image function. This includes the use of the breaks argument for an unequal color scale.
add If true add image and a legend strip to the existing plot.
nlevel Number of color levels used in legend strip
legend.shrink Amount to shrink the size of legend relative to the full height or width of the plot.
legend.width Width in characters of the legend strip. Default is 1.2, a little bigger that the width of a character.
legend.mar Width in characters of legend margin that has the axis. Default is 5.1 for a vertical legend and 3.1 for a horizontal legend.
graphics.reset If FALSE (default) the plotting region ( plt in par) will not be reset and one can add more information onto the image plot. (e.g. using functions such as points or lines.) If TRUE will reset plot parameters to the values before entering the function.
horizontal If false (default) legend will be a vertical strip on the right side. If true the legend strip will be along the bottom.
bigplot Plot coordinates for image plot. If not passed these will be determined within the function.
smallplot Plot coordinates for legend. If not passed these will be determined within the function.
legend.only If TRUE just add the legend to a the plot in the plot region defined by the coordinates in smallplot. In the absence of other information the range for the legend is determined from the zlim argument.
col Color table to use for image ( see help file on image for details). Default is a pleasing range of 64 divisions suggested by Tim Hoar and is similar to the MATLAB (TM) jet color scheme.
lab.breaks If breaks are supplied these are text string labels to put at each break value. This is intended to label axis on a transformed scale such as logs.
axis.args Additional arguments for the axis function used to create the legend axis. (See example below adding a log scaling.)


If the z component is a matrix then the user should be aware that this function locates the matrix element z[i,j] at the grid locations (x[i], y[j]) this is very different 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. What does one do if you don't really have the "z" values on a regular grid? See the functions quilt.plot.Rd and as.image to discretize irregular observations to a grid.

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.

legend.width and legend.mar are in character spaces. These units are helpful in thinking about axis labels that will be put into these areas. To add more or less space between the legend and the image plot alter the mar parameters. The default mar settings (5.1,5.1,5.1,2.1) leaves 2.1 spaces for vertical legends and 5.1 spaces for horizontal legends. Changing the plot margins directly replaces the offset argument in the older version of this function.

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 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. levelplot that is part of the lattice package has a very similar function to image.plot and a formula syntax in the call.

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 elements 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 images with image and then use image.plot to add a legend to the last plot. (See example below for messing with the outer margins to make this work.) Usually a square plot (pty="s") done in a rectangular plot region will have room for the legend stuck to the right side without any other adjustments. See the example below and the code for plot.Wimage for more complicated arrangements of multiple image plots and summary legends.

Note that to add just the legend strip all the numerical information one needs is the zlim argument! We like tim.colors as a default color scale. The the topographic color scale (topo.colors) is also a close second 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.

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.

See Also

image,filled.contour, quilt.plot, plot.surface, add.image, colorbar.plot, tim.colors


x<- 1:10; y<- 1:15; z<- outer( x,y,"+") 

# 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)

# adding breaks and distinct colors
#        (lab.breaks are optional)

brk<- quantile( c(z))
image.plot(x,y,z, breaks=brk, col=rainbow(4), 

#fat (5 characters wide) and short (50% of figure)  color bar on the bottom
   image.plot( x,y,z,legend.width=5, legend.shrink=.5, horizontal=TRUE) 


# Here is quick but quirky way to add a common legend to several plots. 
# The idea is leave some room in the margin and then over plot in this margin

par(oma=c( 0,0,0,4)) # margin of 4 spaces width at right hand side
set.panel( 2,2) # 2X2 matrix of plots

# now draw all your plots using usual image command
for (  k in 1:4){
image( matrix( rnorm(150), 10,15), zlim=c(-4,4), col=tim.colors())

par(oma=c( 0,0,0,1))# reset margin to be much smaller.
image.plot( legend.only=TRUE, zlim=c(-4,4)) 

# image.plot tricked into  plotting in margin of old setting 

set.panel() # reset plotting device

# Here is a more learned strategy to add a common legend to a panel of
# plots  consult the split.screen help file for more explanations.
# For this example we  draw two
# images top and bottom and add a single legend color bar on the right side 

# first divide screen into the figure region and legend colorbar on the 
# right to 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),

   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
## Not run: 
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,
## End(Not run)
# sorting out the 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="grey")

# "columns" of A are horizontal and rows are ordered from bottom to top!
# matrix in its usual tabular form where the rows are y  and columns are x

image.plot( t( A[6:1,]), axes=FALSE)


[Package fields version 3.3.1 Index]