Below is a 'pretty-poor' version of a color picker I wrote using the
code on the color chart page I cited. It's slightly 'pretty' in terms
of layout, but 'poor' in terms of usability and flexibility. Still,
it is more useful to me than the nearly-null set of alternatives
I have found in R. Maybe someone else can do better.
[Some lines below have been broken by my mail client.]
# Using code from http://research.stowers-institute.org/efg/R/Color/Chart/
colorpicker <- function(n, order=c("index", "hue"), cols=colors(),
value=c("name", "index")) {
## n: max number of colors to pick (default: as many are selected in
identify)
## order: how to order the colors in cols
## cols: vector of colors
## value: return color names or indices in cols?
SetTextContrastColor <- function(color)
{
ifelse( mean(col2rgb(color)) > 127, "black", "white")
}
# Define this array of text contrast colors that corresponds to each
# member of the colors() array.
TextContrastColor <- unlist( lapply(cols, SetTextContrastColor) )
ncolors <- length(cols)
if (missing(n)) n <- ncolors
# store coordinates of centers
x <- vector("integer", length=0)
y <- vector("integer", length=0)
ind <- vector("integer", length=0)
nr <- ceiling(sqrt(ncolors))
nc <- ceiling( ncolors/nr )
order <- match.arg(order)
value <- match.arg(value)
if (order=="index") {
# 1a. Plot matrix of R colors, in index order, nc per row.
# This example plots each row of rectangles one at a time.
plot( c(1,nc), c(0,nr), type="n", ylab="", xlab="",
axes=FALSE, ylim=c(nr,0))
title("R colors (index order): LT click to select; RT click to end")
for (j in 0:(nr-1))
{
base <- j*nc
remaining <- length(cols) - base
RowSize <- ifelse(remaining < nc, remaining, nc)
x <- c(x, 1:RowSize)
y <- c(y, rep(j, RowSize))
ind <- c(ind, base + (1:RowSize))
rect((1:RowSize)-0.5,j-0.5, (1:RowSize)+0.5,j+0.5,
border="black",
col=cols[base + (1:RowSize)])
text((1:RowSize), j, paste(base + (1:RowSize)), cex=0.7,
col=TextContrastColor[base + (1:RowSize)])
}
}
else ## if (order=="hue")
{
# 1b. Plot matrix of R colors, in "hue" order, nc per row.
# This example plots each rectangle one at a time.
RGBColors <- col2rgb(cols[1:length(cols)])
HSVColors <- rgb2hsv( RGBColors[1,], RGBColors[2,], RGBColors[3,],
maxColorValue=255)
HueOrder <- order( HSVColors[1,], HSVColors[2,], HSVColors[3,] )
plot(0, type="n", ylab="", xlab="",
axes=FALSE, ylim=c(nr,0), xlim=c(1,nc))
title("R colors (HSV order): LT click to select; RT click to end")
for (j in 0:(nr-1))
{
for (i in 1:nc)
{
k <- j*nc + i
if (k <= length(cols))
{
x <- c(x, i)
y <- c(y, j)
ind <- c(ind, HueOrder[k] )
rect(i-0.5,j-0.5, i+0.5,j+0.5, border="black", col=cols[
HueOrder[k] ])
text(i,j, paste(HueOrder[k]), cex=0.7, col=TextContrastColor[
HueOrder[k] ])
}
}
}
}
## use identify to select n colors
result <- identify(x, y, ind, n=n, offset=-1, pos=FALSE)
result <- if (value=="index") result else cols[result]
result
}
Greg Snow wrote:
I don't know of any existing palettes that meet your conditions, but here are a
couple of options for interactive exploration of colorsets (this is quick and
dirty, there are probably some better orderings, base colors, etc.):
colpicker <- function( cols=colors() ) {
n <- length(cols)
nr <- ceiling(sqrt(n))
nc <- ceiling( n/nr )
imat <- matrix(c(seq_along(cols), rep(NA, nr*nc-n) ),
ncol=nc, nrow=nr)
image( seq.int(nr),seq.int(nc), imat, col=cols, xlab='', ylab='' )
xy <- locator()
cols[ imat[ cbind( round(xy$x), round(xy$y) ) ] ]
}
colpicker()
## another approach
library(TeachingDemos)
cols <- colors()
n <- length(cols)
par(xpd=TRUE)
# next line only works on windows
HWidentify( (1:n) %% 26, (1:n) %/% 26, label=cols, col=cols, pch=15, cex=2 )
# next line works on all platforms with tcltk
HTKidentify( (1:n) %% 26, (1:n) %/% 26, label=cols, col=cols, pch=15, cex=2 )
# reorder
cols.rgb <- col2rgb( cols )
d <- dist(t(cols.rgb))
clst <- hclust(d)
colpicker(cols[clst$order])
HWidentify( (1:n) %% 26, (1:n) %/% 26, label=cols[clst$order],
col=cols[clst$order], pch=15, cex=2 )
## or HTKidentify
cols.hsv <- rgb2hsv( cols.rgb )
d2 <- dist(t(cols.hsv))
clst2 <- hclust(d2)
HWidentify( (1:n) %% 26, (1:n) %/% 26, label=cols[clst2$order],
col=cols[clst2$order], pch=15, cex=2 )
## or HTKidentify
Hope this helps,
--
Michael Friendly Email: friendly AT yorku DOT ca
Professor, Psychology Dept.
York University Voice: 416 736-5115 x66249 Fax: 416 736-5814
4700 Keele Street http://www.math.yorku.ca/SCS/friendly.html
Toronto, ONT M3J 1P3 CANADA
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