image.plot {fields} | R Documentation

## Draws image plot with a legend strip for the color scale based on either a regular grid or a grid of quadrilaterals.

### 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. It also allows for plotting quadrilateral cells in the image format that often arise from regular grids transformed with a map projection.

### Usage

    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)

### Arguments

`...` | 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. The basic concept is that the coordinates of x and y still define a grid but the cells are just quadrilaterals raterh being restricted to rectangles.
`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` | This option for the case of unequally spaced grids with x and y being matrices of grid point locations. If FALSE (default) the quadralaterals will be extended to surround the z locations as midpoints. If TRUE z values will be averaged to yield a midpoint value and the original grid points be used to define the quadralaterals. (See help on poly.image for details). In most cases midpoint should be FALSE to preserve exact values for z and let the grid polygons be modified.

### Details

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.

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

### Examples

    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)

[Package fields version 6.01 Index]