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colorbar.plot

Adds color scale strips to an existing plot.


Description

Adds one or more color scales in a horizontal orientation, vertical orientation to an existing plot.

Usage

colorbar.plot(x, y, strip, strip.width = 0.1, strip.length = 4 * strip.width, 
zrange = NULL, adj.x = 0.5, adj.y = 0.5, col = tim.colors(256), 
horizontal = TRUE, ...)

Arguments

x

x position of strip in user coordinates

y

y position of strip in user coordinates

strip

Either a vector or matrix giving the values of the color strip(s). If a matrix then strips are assumed to be the columns.

strip.width

Width of strip as a fraction of the plotting region.

strip.length

Length of strip as a function of the plotting region. Default is a pleasing 8 times width.

zrange

If a vector these are the common limits used for assigning the color scale. Default is to use the range of values in strip. If a two column matrix, rows are used as the limits for each strip.

adj.x

Location of strip relative to x coordinate. Most common values are .5 (centered), 0 (right end at x) and 1 (left end of at x). These are the same conventions that are used for adj in positioning text.

adj.y

Location of strip relative to y coordinate. Same rules as adj.x

col

Color table used for strip. Default is our favorite tim.colors being a scale from a dark blue to dark red.

horizontal

If TRUE draws strips horizontally. If FALSE strips are drawn vertically

...

optional graphical arguments that are passed to the image function.

Details

This function draws the strips as a sequence of image plots added to the existing plot. The main work is in creating a grid ( x,y) for the image that makes sense when superimposed on the plot. Note that although the columns of strip are considered as separate strips these can be oriented either horizontally or vertically based on the value of horizontal. The rows of zrange are essentially the zlim argument passed to the image function when each strip is drawn.

Don't forget to use locator to interactively determine positions. text can be used to label points neatly in conjunction with setting adj.x and adj.y. Although this function is inefficient for placing images at arbitrary locations on a plot the code can be easily adapted to do this.

This function was created to depict univariate posterior distribution on a map. The values are quantiles of the distribution and the strips when added under a common color scale give an overall impression of location and scale for several distributions.

Author(s)

Doug Nychka

See Also

image.plot, arrow.plot, add.image

Examples

# set up a plot but don't plot points  and no "box"
plot( 1:10, (1:10)*10, type="n", bty="n") 
# of course this could be anything 

y<- cbind( 1:15, (1:15)+25)

colorbar.plot( 2.5, 30, y)
points( 2.5,30, pch="+", cex=2, adj=.5)
# note that strip is still in 1:8 aspect even though plot has very 
# different ranges for x and y. 

# adding legend using image.plot
zr<- range( c( y))
image.plot( legend.only=TRUE, zlim= zr) 
# see help(image.plot) to create more room in margin etc. 

zr<- rbind( c(1,20), c(1,100)) # separate ranges for columns of y. 
colorbar.plot( 5, 70, y, adj.x=0, zrange= zr)
# some reference lines to show placement
xline( 5, lty=2) # strip starts at x=5 
yline(70, lty=2)  # strip is centered around y=7 (because adj.y=.5 by default)

# many strips on common scale.

y<- matrix( 1:200, ncol=10)
colorbar.plot( 2, 75, y, horizontal=FALSE, col=rainbow(256)) 

# Xmas strip
y<- cbind( rep( c(1,2),10))
y[15] <- NA # NA's should work 
colorbar.plot( 6, 45, y, adj.y=1,col=c("red", "green"))
text(6,48,"Christmas strip", cex=2)

# lennon thumbnail
# there are better ways to this ... see add.image for example.
data( lennon)
colorbar.plot( 7.5,22, lennon, 
           strip.width=.25, strip.length=.25, col=grey(seq( 0,1,,256)))

fields

Tools for Spatial Data

v11.6
GPL (>= 2)
Authors
Douglas Nychka [aut, cre], Reinhard Furrer [aut], John Paige [aut], Stephan Sain [aut], Florian Gerber [aut], Matthew Iverson [aut], University Corporation for Atmospheric Research [cph]
Initial release
2020-10-06

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