Some useful color tables for images and tools to handle them.
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() snow.colors(n=256, alpha=1) 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 Mattlab 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
https://github.com/dnychka/MJProject.) larry.colors
is a 13 color palette used by Larry McDaniel (retired software engineer from NCAR) and is particularly
useful for visualizing fields of climate variables.
snow.colors
is the scale used by Will Klieber's team for
visualizing snow cover from remotely sensed data products. See the commented code for the script as to how how this was formed from an orignal raw 256 level scale. Note the that first color in this table is grey and is desigend to represent the minimum value of the range ( e.g. 0). If the image in in percent snow cover then zlim=c(0,100)
would make sense as a range to fit grey pixels to zero and white to 100 percent.
designer.color
is the master function for the otther scales.
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. See also colorBrewer to choose sequences of colors that form a good palette.
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 examine 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" # view some color table choices set.panel( 4,1) fieldsPlotColors( tim.colors()) title("tim.colors") fieldsPlotColors( larry.colors()) title("larry.colors") fieldsPlotColors( two.colors()) title("two.colors") fieldsPlotColors( snow.colors()) title("snow.colors") # a bubble plot with some transparency for overlapping dots set.seed(123) loc<- matrix( rnorm( 200), 100,2) Z<- loc[,1] + loc[,2] colorMap<- color.scale( Z, col=tim.colors(10, alpha=.8)) par( mar=c(5,5,5,5)) # extra room on right for color bar plot( loc, col=colorMap, pch=16, cex=2) # add a color scale image.plot(legend.only=TRUE, zlim=range( Z), col=tim.colors(10)) # using tranparency without alpha the image plot would cover points obj<- list( x= 1:8, y=1:10, z= outer( 1:8, 1:10, "+") ) plot( 1:10,1:10) 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(obj$z), c(0,.25,.5,.75,1.0) ) # scale these to [0,1] zr<- range( c(obj$z)) x<- (x-zr[1])/ (zr[2] - zr[1]) coltab<- designer.colors(256,rainbow(5), x) image( obj$z, col= coltab ) # see image.plot for adding all kinds of legends set.panel()
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