adegenet (version 2.0.0)

colorplot: Represents a cloud of points with colors

Description

The colorplot function represents a cloud of points with colors corresponding to a combination of 1,2 or 3 quantitative variables, assigned to RGB (Red, Green, Blue) channels. For instance, this can be useful to represent up to 3 principal components in space. Note that the property of such representation to convey multidimensional information has not been investigated. colorplot is a S3 generic function. Methods are defined for particular objects, like spca objects.

Usage

colorplot(...)
## S3 method for class 'default':
colorplot(xy, X, axes=NULL, add.plot=FALSE, defaultLevel=0, transp=FALSE, alpha=.5, \dots)

Arguments

xy

a numeric matrix with two columns (e.g. a matrix of spatial coordinates.

X

a matrix-like containing numeric values that are translated into the RGB system. Variables are considered to be in columns.

axes

the index of the columns of X to be represented. Up to three axes can be chosen. If null, up to the first three columns of X are used.

add.plot

a logical stating whether the colorplot should be added to the existing plot (defaults to FALSE).

defaultLevel

a numeric value between 0 and 1, giving the default level in a color for which values are not specified. Used whenever less than three axes are specified.

transp

a logical stating whether the produced colors should be transparent (TRUE) or not (FALSE, default).

alpha

the alpha level for transparency, between 0 (fully transparent) and 1 (not transparent); see ?rgb for more details.

...

further arguments to be passed to other methods. In colorplot.default, these arguments are passed to plot/points functions. See ?plot.default and ?points.

Value

• Invisibly returns a vector of colours used in the plot.

Examples

# a toy example
xy <- expand.grid(1:10,1:10)
df <- data.frame(x=1:100, y=100:1, z=runif(100,0,100))
colorplot(xy,df,cex=10,main="colorplot: toy example")

# a genetic example using a sPCA
if(require(spdep)){
data(spcaIllus)
dat3 <- spcaIllus$dat3
spca3 <- spca(dat3,xy=dat3$other$xy,ask=FALSE,type=1,plot=FALSE,scannf=FALSE,nfposi=1,nfnega=1)
colorplot(spca3, cex=4, main="colorplot: a sPCA example")
text(spca3$xy[,1], spca3$xy[,2], dat3$pop)
mtext("P1-P2 in cline\tP3 random \tP4 local repulsion")
}