PlotFaces: Chernoff Faces

In DescTools: Tools for Descriptive Statistics

Chernoff Faces

Description

Plot Chernoff faces. The rows of a data matrix represent cases and the columns the variables.

Usage

PlotFaces(xy, which.row, fill = FALSE, nr, nc,
          scale = TRUE, byrow = FALSE, main, labels, col = "white")

Arguments

xy	xy data matrix, rows represent individuals and columns attributes.
which.row	defines a permutation of the rows of the input matrix.
fill	logic. If set to TRUE, only the first nc attributes of the faces are transformed, nc is the number of columns of x.
nr	number of columns of faces on graphics device
nc	number of rows of faces
scale	logic. If set to TRUE, attributes will be normalized.
byrow	if(byrow==TRUE), x will be transposed.
main	title.
labels	character strings to use as names for the faces.
col	a vector of colors used for the parts of the faces. Colors are recycled in the order: "nose", "eyes", "hair", "face", "lips", "ears". Default is NA, which will omit colors.

Details

The features paramters of this implementation are:

• 1 height of face

• 2 width of face

• 3 shape of face

• 4 height of mouth

• 5 width of mouth

• 6 curve of smile

• 7 height of eyes

• 8 width of eyes

• 9 height of hair

• 10 width of hair

• 11 styling of hair

• 12 height of nose

• 13 width of nose

• 14 width of ears

• 15 height of ears

For details look at the literate program of faces

Value

information about usage of variables for face elements is returned invisibly

Note

based on version 12/2009

Author(s)

H. P. Wolf, some changes Andri Signorell <[e-mail]>

References

Chernoff, H. (1973) The use of faces to represent statistiscal assoziation, JASA, 68, pp 361–368.

The smooth curves are computed by an algorithm found in:
Ralston, A. and Rabinowitz, P. (1985) A first course in numerical analysis, McGraw-Hill, pp 76ff.

Examples

PlotFaces(rbind(1:3,5:3,3:5,5:7))

data(longley)
PlotFaces(longley[1:9,])

set.seed(17)
PlotFaces(matrix(sample(1:1000,128,), 16, 8), main="random faces")


means <- lapply(iris[,-5], tapply, iris$Species, mean)
m <- t(do.call(rbind, means))
m <- cbind(m, matrix(rep(1, 11*3), nrow=3))

# define the colors, first for all faces the same
col <- replicate(3, c("orchid1", "olivedrab", "goldenrod4",
                      "peachpuff", "darksalmon", "peachpuff3"))
rownames(col) <- c("nose","eyes","hair","face","lips","ears")
# change haircolor individually for each face
col[3, ] <- c("lightgoldenrod", "coral3", "sienna4")

z <- PlotFaces(m, nr=1, nc=3, col=col)

# print the used coding
print(z$info, right=FALSE)

DescTools documentation built on Sept. 26, 2024, 1:07 a.m.