In response to my post about colour wheels, I received a suggested enhancement from Drew. The idea is to first match colours based on the text provided and then add nearby colours. This can be done by ordering colours in terms of hue, saturation, and value. The result is a significant improvement and it will capture all of those colours with more obscure names.

Here is my variant of Drew’s function:

col.wheel <- function(str, nearby=3, cex=0.75) {
	cols <- colors()
	hsvs <- rgb2hsv(col2rgb(cols))
	srt <- order(hsvs[1,], hsvs[2,], hsvs[3,])
	cols <- cols[srt]
	ind <- grep(str, cols)
	if (length(ind) <1) stop("no colour matches found",
		call.=FALSE)
	s.ind <- ind
	if (nearby>1) for (i in 1:nearby) {
		s.ind <- c(s.ind, ind+i, ind-i)
	}
	ind <- sort(unique(s.ind))
	ind <- ind[ind <= length(cols)]
	cols <- cols[ind]
	pie(rep(1, length(cols)), labels=cols, col=cols, cex=cex)
	cols
}

I have included an additional parameter, nearby, which specifies the range of additional colours to include. A setting of 1 will include colours matching the specified string and also one colour on either side of each of these. By default, nearby is set to 3.

The wheel below shows the results for col.wheel(“thistle”, nearby=5). As well as the various shades of “thistle”, this also uncovers “plum” and “orchid”.

This is far more powerful than the original function: thanks Drew.

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