(gg)plotting colours in CIELAB space?

[John McCallum]

Hi

 

{Firstly many thanks Hadley for providing us with such an inspiring graphics tool!}

 

I wish to plot data points from colorimetric measurements made in CIELAB colour space on an a* b* scatterplot with point colour mapped to L*a*b* colour.

I have been able to achieve this using colorspace and lattice libraries but have as yet been unable to do this in ggplot2 with scale_identity

 

What originally inspired me was Hadleys figure 6.11  in “Elegant graphics..”  showing the idea in Luv space.

 

Does anyone have code examples for this kind of thing (or for this figure) or of scale_identity usage they could share?

 

Regards

John McCallum

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[Juan Carlos Borrás]

If the number of categorical variables to plot is known beforehand (i.e. a discrete scale) one could try something 

like this (asuming RGB rather than L*a*b*):

f <- function() {c('#000000', '#FF0000', '#00FF00', '#0000FF', '#FFFF00')}

df=data.frame(x=seq(1,7), y=seq(11,17))

ggplot(df)+geom_bar(aes(x=x, y=y, fill=factor(y)), stat="identity")+scale_fill_manual(values=f())

Parametrizing f to return varying lengths is trivial. Mapping L*a*b* tuples to RGB is left as an exercise to the reader ;-)

A scale_color_Lab() function can't be seen in the docs but such hypothetical function wouldn't differ much from scale_color_hue() IMHO.

This answer is penitence from yesterday's blunder though....

Cheers,

jcb!

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[Hadley Wickham]

Hi John,

It should be pretty trivial if you already have the colours as hex (e.g. hex(LAB(l, a, b))) and you're using scale_colour_identity.  Could you please supply a small reproducible example (https://github.com/hadley/devtools/wiki/Reproducibility) ?

Hadley 

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[Brandon Hurr]

I made this a while ago. It takes La*b* and does some math to get hex values (among others). 

Supply it with a data frame that has columns called L, a, and b and it'll go to town. 

I could probably clean it up and make it a bit faster without loops, but it does what I need it to do. The calculations are based upon the equations at easyRGB.com with one tweak when values were < 0. 

Brandon. 

On Tue, Feb 12, 2013 at 6:05 AM, LV <lva...@gmail.com> wrote:

So here are two attempts to replicate figure 6.11 and neither gives anything close to that image:

myColors <- data.frame("L"=runif(10000, 0,100),"a"=runif(10000, -100, 100),"b"=runif(10000, -100, 100))

myColors <- within(myColors, LAB <- hex(LAB(L, a, b)))

myColors <- within(myColors, Luv <- hex(LUV(L, a, b)))

myColors <- na.omit(myColors)

g <- ggplot(myColors, aes(a, b, color=Luv), size=2)

g + geom_point() + ggtitle ("mycolors")

other <- data.frame("L"=runif(10000),"a"=runif(10000),"b"=runif(10000))

other <- within(other, Luv <- hex(LUV(L, a, b)))

other <- na.omit(other)

g <- ggplot(other, aes(a, b, color=Luv), size=2)

g + geom_point() + ggtitle("other")

The first has some diagonal clustering of the dots, the second is pure random dots. 

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[LV]

That's a very nice function, and will have a good look at it. In the meantime, another user posted a solution over at SO. I am pasting it here in case somebody comes across this question in the future: 

http://stackoverflow.com/questions/14826686/