| tim.colors {fields} | R Documentation |
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.
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,...)
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. |
n |
Number of color levels. The setting |
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 |
x |
Positions of colors on a [0,1] scale. Default is to assume that the x values are equally spacesd from 0 to 1. |
z |
Real vector to encode in a color table. |
zlim |
Range to use for color scale. Default is the
|
transparent.color |
Color value to use for NA's or values outside
|
eps |
A small inflation of the range to avoid boundary values of
|
... |
Additional plotting arguments to codeimage.plot |
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.
A vector giving the colors in a hexadecimal format, two extra hex digits are added for the alpha channel.
topo.colors, terrain.colors, image.plot, quilt.plot, grey.scale, fields.color.picker
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()