image.plot {fields} | R Documentation |
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. It also allows for plotting quadrilateral cells in the image format that often arise from regular grids transformed with a map projection.
image.plot(..., add = FALSE, nlevel = 64, horizontal = FALSE, legend.shrink = 0.9, legend.width = 1.2, legend.mar = ifelse(horizontal, 3.1, 5.1), legend.lab = NULL, graphics.reset = FALSE, bigplot = NULL, smallplot = NULL, legend.only = FALSE, col = tim.colors(nlevel), lab.breaks = NULL, axis.args = NULL, legend.args = NULL, midpoint=FALSE)
... |
The usual arguments to the image function. This includes the use of the breaks argument for an unequal color scale. If a quadrilateral grid arguments must be explicitly x,y and z with x, and y being matrices of dimension equal or one more than z giving the grid locations. |
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. |
legend.lab |
Label for the axis of the color legend. Default is no label as this is usual evident from the plot title. |
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.) |
legend.args |
Arguments for a complete specification of the legend label. This is in the form of list and is just passed to the mtext function. Usually this will not be needed. (See example below.) |
midpoint |
If FALSE (default) for quadrilateral grids grid point will be extended to include z locations as midpoints. If true z values will be averaged to yield a midpoint value. (See help on poly.image for details). In most cases midpoint should be FALSE to preserve exact values for z. |
Relationship of x, y and z:
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 discretise
irregular observations to a grid.
If x and y are matrices then
z[i,j] is rendered at a quadrilateral that is centered at x[i,j] and
y[i,j] (midpoint
TRUE). The details of how this cell is found
are buried in poly.image
. If midpoint
is FALSE then x
and y are interpreted as the corners of the quadrilateral cells. But
what about z? The four values of z are now averaged to represent a
value at the midpoint of the cell and this is what is used for
plotting. Quadrilateral grids was added to help with plotting
the gridded output of geophysical models where the regular grid is
defined according to one map projection by the plotting is required
in another projection. Typically the regular grid becomes distorted in
a smooth way when this happens. See the regional climate example for
a illustration of this application.
Fine tuning color scales: This function gives some flexibility in
tuning the color scale to fit the rendering of z values. This can
either be specially designed color scale with specific colors ( see
help on designer.colors
), positioning the colors at specific
points on the [0,1] scale, or mapping distinct colors to intervals of
z. The examples below show how to do each of these. In addition by
supplying lab.break
strings or axis parameters one can
annotate the legend axis in an informative matter.
Dividing up the plotting real estate: It is surprising how hard it is 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 units of 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 reset.graphics=TRUE
to avoid the plotting size
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.
How this function works:
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 examples below and the code for plot.Wimage
for more complicated arrangements of multiple image plots and summary
legends.
Adding just the legend strip:
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 and designer.colors
to "roll
your own". One nice option of this last one is to fix colors at
particular quantiles of the data rather than at equally spaced
intervals. For color choices see how the nlevels
argument figures
into the legend and main plot number of colors.
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.
image,poly.image,filled.contour, quilt.plot, plot.surface, add.image, colorbar.plot, tim.colors
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) image.plot(x,y,z, legend.lab="inches") # adding breaks and distinct colors for intervals of z # with and without lab.breaks brk<- quantile( c(z)) image.plot(x,y,z, breaks=brk, col=rainbow(4)) # annotate legend strip just at break values image.plot(x,y,z, breaks=brk, col=rainbow(4), lab.breaks=names(brk)) # # compare to quantile(c(z), c( .05, .1,.5, .9,.95))-> zp image.plot(x,y,z, axis.args=list( at=zp, labels=names(zp) ) ) # a log scaling for the colors ticks<- c( 1, 2,4,8,16,32) image.plot(x,y,log(z), axis.args=list( at=log(ticks), labels=ticks)) # see help file for designer.colors to generate a color scale that adapts to # quantiles of z. # #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) # adding label with all kinds of additional arguments. # use side=4 for vertical legend and side= 1 for horizontal legend # to be parallel to axes. See help(mtext). image.plot(x,y,z, legend.args=list( text="unknown units", col="magenta", cex=1.5, side=4, line=2)) #### example using a irregular quadrilateral grid data( RCMexample) image.plot( RCMexample$x, RCMexample$y, RCMexample$z[,,1]) #### multiple images with a common legend set.panel() # 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), 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 ## 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, col=topo.colors(64)) ## 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)