triplot: Barycentric plots

In klaR: Classification and Visualization

Barycentric plots

Description

Function to produce triangular (barycentric) plots illustrating proportions of 3 components, e.g. discrete 3D-distributions or mixture fractions that sum up to 1.

Usage

triplot(x = NULL, y = NULL, z = NULL, main = "", frame = TRUE, 
    label = 1:3, grid = seq(0.1, 0.9, by = 0.1), center = FALSE, 
    set.par = TRUE, ...)

Arguments

x	Vector of fractions of first component OR 3-column matrix containing all three components (omitting y and z) OR 3-element vector (for all three components, omitting y and z).
y	(Optional) vector of fractions of second component.
z	(Optional) vector of fractions of third component.
main	Main title
frame	Controls whether a frame (triangle) and labels are drawn.
label	(Character) vector of labels for the three corners.
grid	Values along which grid lines are to be drawn (or FALSE for no grid at all). Default is steps of 10 percent.
center	Controls whether or not to draw centerlines at which there is a ‘tie’ between any two dimensions (see also centerlines).
set.par	Controls whether graphical parameter mar is set so the plot fills the window (see par).
...	Further graphical parameters passed to trilines.

Details

The barycentric plot illustrates the set of points (x,y,z) with x,y,z between 0 and 1 and x+y+z=1; that is, the triangle spanned by (1,0,0), (0,1,0) and (0,0,1) in 3-dimensional space. The three dimensions x, y and z correspond to lower left, upper and lower right corner of the plot. The greater the share of x in the proportion, the closer the point is to the lower left corner; Points on the opposite (upper right) side have a zero x-fraction. The grid lines show the points at which one dimension is held constant, horizontal lines for example contain points with a constant second dimension.

Author(s)

Christian Röver, [e-mail]

See Also

tripoints, trilines, triperplines, trigrid, triframe for points, lines and layout, tritrafo for placing labels, and quadplot for the same in 4 dimensions.

Examples

# illustrating probabilities: 
triplot(label = c("1, 2 or 3", "4 or 5", "6"), 
    main = "die rolls: probabilities", pch = 17)
triperplines(1/2, 1/3, 1/6)

# expected... 
triplot(1/2, 1/3, 1/6, label = c("1, 2 or 3", "4 or 5", "6"), 
    main = "die rolls: expected and observed frequencies", pch = 17)
# ... and observed frequencies. 
dierolls <- matrix(sample(1:3, size = 50*20, prob = c(1/2, 1/3, 1/6), 
                          replace = TRUE), ncol = 50)
frequencies <- t(apply(dierolls, 1, 
    function(x)(summary(factor(x, levels = 1:3)))) / 50)
tripoints(frequencies)

# LDA classification posterior: 
data(iris)
require(MASS)
pred <- predict(lda(Species ~ ., data = iris),iris)
plotchar <- rep(1,150)
plotchar[pred$class != iris$Species] <- 19
triplot(pred$posterior, label = colnames(pred$posterior), 
        main = "LDA posterior assignments", center = TRUE, 
        pch = plotchar, col = rep(c("blue", "green3", "red"), rep(50, 3)), 
        grid = TRUE)
legend(x = -0.6, y = 0.7, col = c("blue", "green3", "red"), 
    pch = 15, legend = colnames(pred$posterior))

klaR documentation built on March 31, 2023, 7:19 p.m.