tim.colors: Some useful color tables for images and tools to handle them.

Description

Several color scales useful for image plots: a pleasing rainbow style color table patterned after that used in Matlab by Tim Hoar and also some simple color interpolation schemes between two or more colors. There is also a function that converts between colors and a real valued vector.

Usage

tim.colors(n = 64, alpha=1.0)
larry.colors()
two.colors(n=256, start="darkgreen", end="red", middle="white",
alpha=1.0)
designer.colors( n=256, col= c("darkgreen", "white", "darkred"), x=
                              seq(0,1,, length(col)) ,alpha=1.0)
color.scale( z, col=tim.colors(256), zlim =NULL,
transparent.color="white", eps= 1e-8)
fieldsPlotColors( col,...)

Arguments

alpha

The transparency of the color -- 1.0 is opaque and 0 is transparent. This is useful for overlays of color and still being able to view the graphics that is covered.

Number of color levels. The setting n=64 is the orignal definition.

start

Starting color for lowest values in color scale

end

Ending color.

middle

Color scale passes through this color at halfway

col

A list of colors (names or hex values) to interpolate

Positions of colors on a [0,1] scale. Default is to assume that the x values are equally spacesd from 0 to 1.

Real vector to encode in a color table.

zlim

Range to use for color scale. Default is the range(z) inflated by 1- eps and 1+eps.

transparent.color

Color value to use for NA's or values outside zlim

eps

A small inflation of the range to avoid boundary values of z being coded as NAs

…

Additional plotting arguments to codeimage.plot

Value

A vector giving the colors in a hexadecimal format, two extra hex digits are added for the alpha channel.

Details

The color in R can be represented as three vectors in RGB coordinates and these coordinates are interpolated separately using a cubic spline to give color values that intermediate to the specified colors.

Ask Tim Hoar about tim.colors! He is a matlab black belt and this is his favorite scale in that system. two.colors is really about three different colors. For other colors try fields.color.picker to view possible choices. start="darkgreen", end="azure4" are the options used to get a nice color scale for rendering aerial photos of ski trails. (See http://www.image.ucar.edu/Data/MJProject.) larry.colors is a 13 color palette used by Larry McDaniel and is particularly useful for visualizing fields of climate variables.

designer.color is the master function for two.colors and tim.colors. It can be useful if one wants to customize the color table to match quantiles of a distribution. e.g. if the median of the data is at .3 with respect to the range then set x equal to c(0,.3,1) and specify three colors to provide a transtion that matches the median value. In fields language this function interpolates between a set of colors at locations x. While you can be creative about these colors just using another color scale as the basis is easy. For example

designer.color( 256, rainbow(4), x= c( 0,.2,.8,1.0))

leaves the choice of the colors to Dr. R after a thunderstorm.

color.scale assigns colors to a numerical vector in the same way as the image function. This is useful to kept the assigment of colors consistent across several vectors by specifiying a common zlim range.

plotColorScale A simple function to plot a vector of colors to examinet their values.

Examples

Run this code

# NOT RUN {
tim.colors(10) 
# returns an array of 10 character strings encoding colors in hex format

# e.g. (red, green,  blue) values of   (16,255, 239)
#   translates to "#10FFEF" 
# rgb( 16/255, 255/255, 239/255, alpha=.5)
#   gives   "#10FFEF80"  note extra "alpha channel"

# veiw some color table choices
set.panel( 2,3)
z<- outer( 1:20,1:20, "+")
obj<- list( x=1:20,y=1:20,z=z )

image( obj, col=tim.colors( 200)) # 200 levels

image( obj, col=two.colors() )

# using tranparency without alpha the image plot would cover points
plot( 1:20,1:20)
image(obj, col=two.colors(alpha=.5), add=TRUE)

coltab<- designer.colors(col=c("blue", "grey", "green"),
                   x= c( 0,.3,1) ) 
image( obj, col= coltab )

# peg colors at some desired quantiles  of data.
# NOTE need 0 and 1 for the color scale to make sense
x<- quantile( c(z), c(0,.25,.5,.75,1.0) )
# scale these to [0,1]
zr<- range( c(z))
x<- (x-zr[1])/ (zr[2] - zr[1])  

coltab<- designer.colors(256,rainbow(5), x)
image( z, col= coltab )
# see image.plot for adding all kinds of legends

# some random color values
set.seed(123)
z<- rnorm(100)
hex.codes<- color.scale(z, col=two.colors())
N<-length( hex.codes)
# take a look at the coded values
# or equivalently create some Xmas wrapping paper!
image( 1:N, N, matrix(1:N, N,1) , col=hex.codes, axes=FALSE,
                               xlab="", ylab="")

set.panel()

# }