triplot function

Barycentric plots

Function to produce triangular (barycentric) plots illustrating proportions of 3 components, e.g. discrete 3D-distributions or mixture fractions that sum up to 1. latin1

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, roever@statistik.tu-dortmund.de

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))