Sorry about the bug. How embarrassing. Especially because I've learned over
the years to trust my gut feelings when something doesn't feel quite right,
and when I was testing the function, I remember thinking "surely there a
better matching named color than 'magenta'".
Thanks for the fix.
Kevin
On Sat, Jun 1, 2013 at 11:30 AM, John Fox <j...@mcmaster.ca> wrote:
> Hi Michael,
>
> This has become a bit of a comedy of errors.
>
> The bug is in Kevin Wright's code, which I adapted, and you too in your
> version, which uses local() rather than function() to produce the closure.
> The matrix which.col contains character data, as a consequence of binding
> the minimum squared distances to colour names, and thus the comparison
> cols.near[2,] < near^2 doesn't work properly when, ironically, the distance
> is small enough so that it's rendered in scientific notation.
>
> Converting to numeric appears to work:
>
> > rgb2col2 <- local({
> + all.names <- colors()
> + all.hsv <- rgb2hsv(col2rgb(all.names))
> + find.near <- function(x.hsv) {
> + # return the nearest R color name and distance
> + sq.dist <- colSums((all.hsv - x.hsv)^2)
> + rbind(all.names[which.min(sq.dist)], min(sq.dist))
> + }
> + function(cols.hex, near=.25){
> + cols.hsv <- rgb2hsv(col2rgb(cols.hex))
> + cols.near <- apply(cols.hsv, 2, find.near)
> + ifelse(as.numeric(cols.near[2,]) <= near^2, cols.near[1,],
> cols.hex)
> + }
> + })
>
> > rgb2col2(c("#010101", "#EEEEEE", "#AA0000", "#00AA00", "#0000AA",
> + "#AAAA00", "#AA00AA", "#00AAAA"))
>
> [1] "black" "gray93" "darkred" "green4" "blue4"
> "darkgoldenrod"
> [7] "darkmagenta" "cyan4"
>
> The same bug is in the code that I just posted using Lab colours, so (for
> posterity) here's a fixed version of that, using local():
>
> > rgb2col <- local({
> + all.names <- colors()
> + all.lab <- t(convertColor(t(col2rgb(all.names)), from = "sRGB",
> + to = "Lab", scale.in = 255))
> + find.near <- function(x.lab) {
> + sq.dist <- colSums((all.lab - x.lab)^2)
> + rbind(all.names[which.min(sq.dist)], min(sq.dist))
> + }
> + function(cols.hex, near = 2.3) {
> + cols.lab <- t(convertColor(t(col2rgb(cols.hex)), from = "sRGB",
> + to = "Lab", scale.in = 255))
> + cols.near <- apply(cols.lab, 2, find.near)
> + ifelse(as.numeric(cols.near[2, ]) < near^2, cols.near[1, ],
> toupper(cols.hex))
> + }
> + })
>
> > rgb2col(c("#010101", "#EEEEEE", "#AA0000", "#00AA00", "#0000AA",
> "#AAAA00", "#AA00AA", "#00AAAA"))
>
> [1] "black" "gray93" "#AA0000" "#00AA00" "#0000AA" "#AAAA00"
> [7] "#AA00AA" "#00AAAA"
>
> > rgb2col(c("#010101", "#EEEEEE", "#AA0000", "#00AA00", "#0000AA",
> "#AAAA00", "#AA00AA", "#00AAAA"), near=15)
>
> [1] "black" "gray93" "firebrick3" "limegreen"
> [5] "blue4" "#AAAA00" "darkmagenta" "lightseagreen"
>
> So with Lab colours, setting near to the JND of 2.3 leaves many of these
> colours unmatched. I experimented a bit, and using 15 (as above) produces
> matches that appear reasonably "close" to me.
>
> I used squared distances to avoid taking the square-roots of all the
> distances. Since the criterion for "near" colours, which is on the distance
> scale, is squared to make the comparison, this shouldn't be problematic.
>
> I hope that finally this will be a satisfactory solution.
>
> Best,
> John
>
> > -----Original Message-----
> > From: r-help-boun...@r-project.org [mailto:r-help-bounces@r-
> > project.org] On Behalf Of Michael Friendly
> > Sent: Saturday, June 01, 2013 11:33 AM
> > To: John Fox
> > Cc: 'r-help'; 'Martin Maechler'
> > Subject: Re: [R] measuring distances between colours?
> >
> > Just a quick note: The following two versions of your function don't
> > give the same results. I'm not sure why, and also not sure why the
> > criterion for 'near' should be expressed in squared distance.
> >
> > # version 1
> > rgb2col <- local({
> > hex2dec <- function(hexnums) {
> > # suggestion of Eik Vettorazzi
> > sapply(strtoi(hexnums, 16L), function(x) x %/% 256^(2:0) %%
> > 256)
> > }
> > findMatch <- function(dec.col) {
> > sq.dist <- colSums((hsv - dec.col)^2)
> > rbind(which.min(sq.dist), min(sq.dist))
> > }
> > colors <- colors()
> > hsv <- rgb2hsv(col2rgb(colors))
> >
> > function(cols, near=0.25) {
> > cols <- sub("^#", "", toupper(cols))
> > dec.cols <- rgb2hsv(hex2dec(cols))
> > which.col <- apply(dec.cols, 2, findMatch)
> > matches <- colors[which.col[1, ]]
> > unmatched <- which.col[2, ] > near^2
> > matches[unmatched] <- paste("#", cols[unmatched], sep="")
> > matches
> > }
> > })
> >
> > # version 2
> > rgb2col2 <- local({
> > all.names <- colors()
> > all.hsv <- rgb2hsv(col2rgb(all.names))
> > find.near <- function(x.hsv) {
> > # return the nearest R color name and distance
> > sq.dist <- colSums((all.hsv - x.hsv)^2)
> > rbind(all.names[which.min(sq.dist)], min(sq.dist))
> > }
> > function(cols.hex, near=.25){
> > cols.hsv <- rgb2hsv(col2rgb(cols.hex))
> > cols.near <- apply(cols.hsv, 2, find.near)
> > ifelse(cols.near[2,] < near^2, cols.near[1,], cols.hex)
> > }
> > })
> >
> > # tests
> > > rgb2col(c("#010101", "#EEEEEE", "#AA0000", "#00AA00", "#0000AA",
> > "#AAAA00", "#AA00AA", "#00AAAA"))
> > [1] "black" "gray93" "darkred" "green4"
> > [5] "blue4" "darkgoldenrod" "darkmagenta" "cyan4"
> > > rgb2col2(c("#010101", "#EEEEEE", "#AA0000", "#00AA00", "#0000AA",
> > "#AAAA00", "#AA00AA", "#00AAAA"))
> > [1] "#010101" "#EEEEEE" "darkred" "green4"
> > [5] "blue4" "darkgoldenrod" "darkmagenta" "cyan4"
> > >
> >
> >
> > On 5/31/2013 7:42 PM, John Fox wrote:
> > > Dear Kevin,
> > >
> > > I generally prefer your solution. I didn't realize that col2rgb()
> > worked
> > > with hex-colour input (as opposed to named colours), so my code
> > converting
> > > hex numbers to decimal is unnecessary; and using ifelse() is clearer
> > than
> > > replacing the non-matches.
> > >
> > > I'm not so sure about avoiding the closure, since for converting
> > small
> > > numbers of colours, your function will spend most of its time
> > constructing
> > > the local function find.near() and building all.hsv. Here's an
> > example,
> > > using your rgb2col() and a comparable function employing a closure,
> > with one
> > > of your examples executed 100 times:
> > >
> > >> r2c <- function(){
> > > + all.names <- colors()
> > > + all.hsv <- rgb2hsv(col2rgb(all.names))
> > > + find.near <- function(x.hsv) {
> > > + # return the nearest R color name and distance
> > > + sq.dist <- colSums((all.hsv - x.hsv)^2)
> > > + rbind(all.names[which.min(sq.dist)], min(sq.dist))
> > > + }
> > > + function(cols.hex, near=.25){
> > > + cols.hsv <- rgb2hsv(col2rgb(cols.hex))
> > > + cols.near <- apply(cols.hsv, 2, find.near)
> > > + ifelse(cols.near[2,] < near^2, cols.near[1,], cols.hex)
> > > + }
> > > + }
> > >
> > >> mycols <- c("#010101", "#EEEEEE", "#AA0000", "#00AA00", "#0000AA",
> > > + "#AAAA00", "#AA00AA", "#00AAAA")
> > >
> > >> system.time(for (i in 1:100) oldnew <- c(mycols, rgb2col(mycols,
> > > near=.25)))
> > > user system elapsed
> > > 1.97 0.00 1.97
> > >
> > >> system.time({rgb2col2 <- r2c()
> > > + for (i in 1:100) oldnew2 <- c(mycols, rgb2col2(mycols,
> > near=.25))
> > > + })
> > > user system elapsed
> > > 0.08 0.00 0.08
> > >
> > >> rbind(oldnew, oldnew2)
> > > [,1] [,2] [,3] [,4] [,5] [,6]
> > > oldnew "#010101" "#EEEEEE" "#AA0000" "#00AA00" "#0000AA" "#AAAA00"
> > > oldnew2 "#010101" "#EEEEEE" "#AA0000" "#00AA00" "#0000AA" "#AAAA00"
> > > [,7] [,8] [,9] [,10] [,11] [,12]
> > > oldnew "#AA00AA" "#00AAAA" "#010101" "#EEEEEE" "darkred" "green4"
> > > oldnew2 "#AA00AA" "#00AAAA" "#010101" "#EEEEEE" "darkred" "green4"
> > > [,13] [,14] [,15] [,16]
> > > oldnew "blue4" "darkgoldenrod" "darkmagenta" "cyan4"
> > > oldnew2 "blue4" "darkgoldenrod" "darkmagenta" "cyan4"
> > >
> > > Does this really make a difference? Frankly, it wouldn't for my
> > application
> > > (for colour selection in the Rcmdr) where a user is likely to perform
> > at
> > > most one or two conversions of a small number of colours in a
> > session. The
> > > time advantage of the second approach will depend upon the number of
> > times
> > > the function is invoked and the number of colours converted each
> > time.
> > >
> > > Best,
> > > John
> > >
> > >> -----Original Message-----
> > >> From: r-help-boun...@r-project.org [mailto:r-help-bounces@r-
> > >> project.org] On Behalf Of Kevin Wright
> > >> Sent: Friday, May 31, 2013 3:39 PM
> > >> To: Martin Maechler
> > >> Cc: r-help; John Fox
> > >> Subject: Re: [R] measuring distances between colours?
> > >>
> > >> Thanks for the discussion. I've also wanted to be able to find
> > nearest
> > >> colors. I took the code and comments in this thread and simplified
> > the
> > >> function even further. (Personally, I think using closures results
> > in
> > >> Rube-Goldberg code. YMMV.) The first example below is what I use
> > for
> > >> 'group' colors in lattice.
> > >>
> > >> Kevin Wright
> > >>
> > >> rgb2col <- function(cols.hex, near=.25){
> > >> # Given a vector of hex colors, find the nearest 'named' R colors
> > >> # If no color closer than 'near' is found, return the hex color
> > >> # Authors: John Fox, Martin Maechler, Kevin Wright
> > >> # From r-help discussion 5.30.13
> > >>
> > >> find.near <- function(x.hsv) {
> > >> # return the nearest R color name and distance
> > >> sq.dist <- colSums((all.hsv - x.hsv)^2)
> > >> rbind(all.names[which.min(sq.dist)], min(sq.dist))
> > >> }
> > >> all.names <- colors()
> > >> all.hsv <- rgb2hsv(col2rgb(all.names))
> > >> cols.hsv <- rgb2hsv(col2rgb(cols.hex))
> > >> cols.near <- apply(cols.hsv, 2, find.near)
> > >> ifelse(cols.near[2,] < near^2, cols.near[1,], cols.hex)
> > >> }
> > >>
> > >> mycols <- c("royalblue", "red", "#009900", "dark orange", "#999999",
> > >> "#a6761d", "#aa00da")
> > >> mycols <- c("#010101", "#EEEEEE", "#AA0000", "#00AA00", "#0000AA",
> > >> "#AAAA00", "#AA00AA", "#00AAAA")
> > >> mycols <- c("#010101", "#090909", "#090000", "#000900", "#000009",
> > >> "#090900", "#090009", "#000909")
> > >> oldnew <- c(mycols, rgb2col(mycols, near=.25)) # Also try near=10
> > >> pie(rep(1,2*length(mycols)), labels=oldnew, col=oldnew)
> > >>
> > >> [[alternative HTML version deleted]]
> > >>
> > >> ______________________________________________
> > >> R-help@r-project.org mailing list
> > >> https://stat.ethz.ch/mailman/listinfo/r-help
> > >> PLEASE do read the posting guide http://www.R-project.org/posting-
> > >> guide.html
> > >> and provide commented, minimal, self-contained, reproducible code.
> > >
> >
> >
> > --
> > Michael Friendly Email: friendly AT yorku DOT ca
> > Professor, Psychology Dept. & Chair, Quantitative Methods
> > York University Voice: 416 736-2100 x66249 Fax: 416 736-5814
> > 4700 Keele Street Web: http://www.datavis.ca
> > Toronto, ONT M3J 1P3 CANADA
> >
> > ______________________________________________
> > R-help@r-project.org mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide http://www.R-project.org/posting-
> > guide.html
> > and provide commented, minimal, self-contained, reproducible code.
>
> ______________________________________________
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
--
Kevin Wright
[[alternative HTML version deleted]]
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
