User functions

Several user functions are available to create a simple graph (stored as an ADEg object in R). Each function creates an object of a given class (see Figure 1). Table 1 lists the different functions, their corresponding classes and a short description. The ade4 users would not be lost: many functions have kept their names in adegraphics. The main changes are listed in Table 2.

Table 1: Graphical functions available in adegraphics

Table 2: Changes in functions names between ade4 and adegraphics

Arguments

The list of arguments of a function are given by the args function.

library(ade4)
library(adegraphics)
args(s.label)

## function (dfxy, labels = rownames(dfxy), xax = 1, yax = 2, facets = NULL, 
##     plot = TRUE, storeData = TRUE, add = FALSE, pos = -1, ...) 
## NULL

Some arguments are very general and present in all user functions:

• plot: a logical value indicating if the graph should be displayed

• storeData: a logical value indicating if the data should be stored in the returned object. If FALSE, only the names of the data are stored. This allows to reduce the size of the returned object but it implies that the data should not be modified in the environment to plot again the graph.

• add: a logical value indicating if the graph should be superposed on the graph already displayed in the current device (it replaces the argument add.plot in ade4).

• pos: an integer indicating the position of the environment where the data are stored, relative to the environment where the function is called. Useful only if storeData is FALSE.

• …: additional graphical parameters (see below)

Some other arguments influence the graphical outputs and they are thus specific to the type of produced graph. Figure 2 summarizes some of these graphical parameters available for the different functions. We only reported the parameters stored in the g.args slot of the returned object (see the Parameters in g.args section).

The ade4 users would note that the names of some arguments have been modified in adegraphics. The Appendix gives a full list of these modifications.

Slots and Methods

A call to a graphical function (see the User functions section) returns an ADEg object. Each object is defined by a number of slots and several methods are associated to this class. Let us consider the olympic data set available in the ade4 package. A principal component analysis (PCA) is applied on the olympic$tab table that contains the results for 33 participating athletes at the 1988 summer olympic games:

data(olympic)
pca1 <- dudi.pca(olympic$tab, scannf = FALSE)

The barplot of eigenvalues is then drawn and stored in g1:

g1 <- s1d.barchart(pca1$eig, p1d.horizontal = F, ppolygons.col = "white")

The class of the g1 object is C1.barchart which extends the ADEg class:

class(g1)

## [1] "C1.barchart"
## attr(,"package")
## [1] "adegraphics"

showClass("C1.barchart")

## Class "C1.barchart" [package "adegraphics"]
## 
## Slots:
##                                                                        
## Name:          data  trellis.par     adeg.par lattice.call       g.args
## Class:         list         list         list         list         list
##                                              
## Name:         stats       s.misc         Call
## Class:         list         list         call
## 
## Extends: 
## Class "ADEg.C1", directly
## Class "ADEg", by class "ADEg.C1", distance 2
## Class "ADEgORtrellis", by class "ADEg.C1", distance 3
## Class "ADEgORADEgSORtrellis", by class "ADEg.C1", distance 3

This object contains different slots:

slotNames(g1)

## [1] "data"         "trellis.par"  "adeg.par"     "lattice.call" "g.args"      
## [6] "stats"        "s.misc"       "Call"

These slots are defined for each ADEg object and contain different types of information. The package adegraphics uses the capabilities of the lattice package to display a graph (by generating a trellis object). Hence, several slots contain information that will be passed in the call to the lattice functions:

• data: a list containing information about the data.

• trellis.par: a list of graphical parameters that are directly passed to the lattice functions using the par.settings argument (see the Parameters in trellis.par section).

• adeg.par: a list of graphical parameters defined in adegraphics. The list of parameters can be obtained using the adegpar function (see the Parameters in adeg.par section).

• lattice.call: a list of two elements containing the information required to create the trellis object: graphictype (the name of the lattice functions that should be used) and arguments (the list of parameter values required to obtain the trellis object).

• g.args: a list containing at least the different values of the graphical arguments described in Figure 2 (see the Parameters in g.args section).

• stats: a list of internal preliminary computations performed to display the graph.

• s.misc: a list of other internal parameters.

• Call: an object of class call containing the matched call.

These different slots can be extracted using the @ operator:

g1@data

## $score
##  [1] 3.4182381 2.6063931 0.9432964 0.8780212 0.5566267 0.4912275 0.4305952
##  [8] 0.3067981 0.2669494 0.1018542
## 
## $at
##  [1]  1  2  3  4  5  6  7  8  9 10
## 
## $frame
## [1] 38
## 
## $storeData
## [1] TRUE

All these slots are automatically filled during the object creation. The trellis.par, adeg.par and g.args can also be modified a posteriori using the update method (see the Customizing a graph section). This allows to customize graphs after their creation.

We consider the correlation circle that depicts the correlation between PCA axes and the results for each event:

g2 <- s.corcircle(pca1$co)

class(g2)

## [1] "S2.corcircle"
## attr(,"package")
## [1] "adegraphics"

g2@g.args

## $fullcircle
## [1] TRUE
## 
## $xlim
## [1] -1.2  1.2
## 
## $ylim
## [1] -1.2  1.2
## 
## $scales
## $scales$draw
## [1] FALSE

The argument fullcircle can be updated a posteriori so that the original object is modified:

update(g2, fullcircle = FALSE)

g2@g.args

## $fullcircle
## [1] FALSE
## 
## $xlim
## [1] -0.8815395  0.9544397
## 
## $ylim
## [1] -0.6344523  1.2015270
## 
## $scales
## $scales$draw
## [1] FALSE

Several other methods have been defined for the ADEg class allowing to extract information, modify or combine objects:

• getcall, getlatticecall and getstats: these accessor methods return respectively the Call, the lattice.call and the stats slots.

• getparameters: this method returns the trellis.par and/or the adeg.par slots.

• show, print and plot: these methods display the ADEg object in the current device or in a new one.

• gettrellis: this method returns the ADEg object as a trellis object. It can then be exploited using the lattice and latticeExtra packages.

• superpose, + and add.ADEg: these methods superpose two ADEg graphs. It returns a multiple graph object of class ADEgS (see the The basic methods for superposition, juxtaposition and insertion section).

• insert: this method inserts an ADEg graph in an existing one or in the current device. It returns an ADEgS object (see the The basic methods for superposition, juxtaposition and insertion section).

• cbindADEg, rbindADEg: these methods combine several ADEg graphs. It returns an ADEgS object (see the The basic methods for superposition, juxtaposition and insertion section).

• update: this method modifies the graphical parameters after the ADEg creation. It updates the current display and returns the modified ADEg (see the Customizing a graph section).

For instance:

getcall(g1) ## equivalent to g1@Call

## s1d.barchart(score = pca1$eig, p1d.horizontal = F, ppolygons.col = "white")

A biplot-like graph can be obtained using the superpose method. The result is a multiple graph:

g3 <- s.label(pca1$li)
g4 <- s.arrow(5 * pca1$c1, add = TRUE)

class(g4)

## [1] "ADEgS"
## attr(,"package")
## [1] "adegraphics"

In addition, some object classes have specific methods. For instance, a zoom method is available for ADEg.S1 and ADEg.S2 classes. For the ADEg.S2 class, the method addhist (see the The basic methods for superposition, juxtaposition and insertion section) decorates a 2-D graph by adding marginal distributions as histograms and density lines (this method replaces and extends the s.hist function of ade4).

zoom(g3, zoom = 2, center = c(2, -2))

Slots and Methods

The class ADEgS is used to store multiple graphs. Different slots are associated to this class (use the symbol @ to extract information):

• ADEglist: a list of graphs stored as trellis, ADEg and/or ADEgS objects.

• positions: a matrix containing the positions of the graphs. It has four columns and as many rows as the number of graphical objects in the ADEglist slot. For each graph (i.e. row), it contains the coordinates of the bottom-left and top-right corners in npc units (i.e. normalized parent coordinates varying between 0 and 1).

• add: a square binary matrix with as many rows and columns as the number of graphical objects in the ADEglist slot. It allows to manage the superposition of graphs: the value at the i-th row and j-th column is equal to 1 if the j-th graphical object is superposed on the i-th. Otherwise, this value is equal to 0.

• Call: an object of class call containing the matched call.

Several methods have been implemented to obtain information, edit or modify ADEgS objects. Several methods are inspired from the management of list in R:

• [, [[ and $: these methods extract one or more elements from the ADEgS object.

• getpositions, getgraphics and getcall: these methods return the positions, the ADEglist and the Call slots, respectively.

• names and length: these methods return the names and number of graphs contained in the object.

• [[<- and names<-: these methods replace a graph or its name in an ADEgS object (acts on the ADEglist slot).

• show, plot and print: these methods display the ADEgS object in the current device or in a new one.

• superpose and +: these methods superpose two graphs. It returns a multiple graph object of class ADEgS (see the The basic methods for superposition, juxtaposition and insertion section).

• insert: this method inserts a graph in an existing one or in the current device. It returns a multiple graph object of class ADEgS (see the The basic methods for superposition, juxtaposition and insertion section).

• cbindADEg, rbindADEg: these methods combine several graphs. It returns an ADEgS object (see the The basic methods for superposition, juxtaposition and insertion section).

• update: this method modifies the names and/or the positions of the graphs contained in an ADEgS object. It updates the current display and returns the modified ADEgS.

We will show in the next sections how these methods can be used to deal with ADEgS objects.

Creating an ADEgS object by hand

The ADEgS objects can be created by easy manipulation of several simple graphs. Some methods (e.g., insert, superpose) can be used to create a compilation of graphs by hand.

fac.score <- factor(olympic$score < 8000, labels = c("MT8000", "LT8000"))

g5 <- s.class(pca1$li, fac.score, col = c("red", "blue"), chullSize = 1, ellipseSize = 0, 
              plabels.cex = 2, pbackground.col = "grey85", paxes.draw = TRUE)

g6 <- superpose(g5, g3, plot = TRUE) ## equivalent to g5 + g3

class(g6)

## [1] "ADEgS"
## attr(,"package")
## [1] "adegraphics"

g5
s.label(pca1$li, add = TRUE)

rbindADEg(cbindADEg(g2, g3), cbindADEg(g5, g6), plot = TRUE)

g7 <- insert(g2, g6, posi = c(0.65, 0.65, 0.95, 0.95))

class(g7)

## [1] "ADEgS"
## attr(,"package")
## [1] "adegraphics"

length(g7)

## [1] 3

names(g7)

## [1] "g1" "g2" "X"

names(g7) <- c("chulls", "labels", "cor")
class(g7[1])

## [1] "ADEgS"
## attr(,"package")
## [1] "adegraphics"

class(g7[[1]])

## [1] "S2.class"
## attr(,"package")
## [1] "adegraphics"

class(g7$chulls)

## [1] "S2.class"
## attr(,"package")
## [1] "adegraphics"

pos.mat <- getpositions(g7)
pos.mat

##           [,1] [,2] [,3] [,4]
##           0.00 0.00 1.00 1.00
##           0.00 0.00 1.00 1.00
## positions 0.65 0.65 0.95 0.95

pos.mat[3,] <- c(0.1, 0.7, 0.3, 0.9)
update(g7, positions = pos.mat)

g7[[3]] <- g1
g7

addhist(g3)

ADEgS(adeglist = list(g2, g3), layout = c(1, 2))

mlay <- matrix(c(1, 1, 0, 1, 1, 0, 0, 0, 2), byrow = T, nrow = 3)
mlay

##      [,1] [,2] [,3]
## [1,]    1    1    0
## [2,]    1    1    0
## [3,]    0    0    2

ADEgS(adeglist = list(g6, g2), layout = mlay)

mpos <- rbind(c(0, 0.3, 0.7, 1), c(0.5, 0, 1, 0.5))
ADEgS(adeglist = list(g3, g5), positions = mpos)

ADEgS(list(g5, g3), add = matrix(c(0, 1, 0, 0), byrow = TRUE, ncol = 2))

Automatic collections

The package adegraphics contains functionalities to create collections of graphs. These collections are based on a simple graph repeated for different groups of individuals, variables or axes. The building process of these collections is quite simple (definition of arguments in the call of a user function) and leads to the creation of an ADEgS object.

data(jv73)
pca2 <- dudi.pca(jv73$morpho, scannf = FALSE)
s.label(pca2$li)

g8 <- s.label(pca2$li, facets = jv73$fac.riv)

length(g8)

## [1] 12

names(g8)

##  [1] "Allaine"   "Audeux"    "Clauge"    "Cuisance"  "Cusancin"  "Dessoubre"
##  [7] "Doubs"     "Doulonnes" "Drugeon"   "Furieuse"  "Lison"     "Loue"

s.class(pca2$li, fac = jv73$fac.riv, col = rainbow(12), facets = jv73$fac.riv)

pca1 <- dudi.pca(olympic$tab, scannf = FALSE, nf = 4)
g9 <- s.corcircle(pca1$co, xax = 1:2, yax = 3:4)

length(g9)

## [1] 4

names(g9)

## [1] "x1y3" "x2y3" "x1y4" "x2y4"

g9@positions

##      [,1] [,2] [,3] [,4]
## [1,]  0.0  0.5  0.5  1.0
## [2,]  0.5  0.5  1.0  1.0
## [3,]  0.0  0.0  0.5  0.5
## [4,]  0.5  0.0  1.0  0.5

dim(pca1$li)

## [1] 33  4

s1d.boxplot(pca1$li, fac.score, col = c("red", "blue"), 
  psub = list(position = "topleft", cex = 2))

s.value(pca2$li, pca2$tab, symbol = "circle")

data(meaudret)
pca3 <- dudi.pca(meaudret$env, scannf = FALSE)
pca4 <- dudi.pca(meaudret$spe, scale = FALSE, scannf = FALSE)
coi1 <- coinertia(pca3, pca4, scannf = FALSE, nf = 3)
g10 <- plot(coi1)

class(g10)

## [1] "ADEgS"
## attr(,"package")
## [1] "adegraphics"

names(g10)

## [1] "Xax"       "Yax"       "eig"       "XYmatch"   "Yloadings" "Xloadings"

g10@Call

## plot.coinertia(x = coi1)

Parameters in trellis.par

The trellis.par slot is a list of parameters that are directly included in the call of functions of the lattice package. The name of parameters and their default value are given by the trellis.par.get function of lattice.

library(lattice)
sort(names(trellis.par.get()))

##  [1] "add.line"          "add.text"          "as.table"         
##  [4] "axis.components"   "axis.line"         "axis.text"        
##  [7] "background"        "box.3d"            "box.dot"          
## [10] "box.rectangle"     "box.umbrella"      "clip"             
## [13] "dot.line"          "dot.symbol"        "fontsize"         
## [16] "grid.pars"         "layout.heights"    "layout.widths"    
## [19] "panel.background"  "par.main.text"     "par.sub.text"     
## [22] "par.title.text"    "par.xlab.text"     "par.ylab.text"    
## [25] "par.zlab.text"     "plot.line"         "plot.polygon"     
## [28] "plot.symbol"       "reference.line"    "regions"          
## [31] "shade.colors"      "strip.background"  "strip.border"     
## [34] "strip.shingle"     "superpose.line"    "superpose.polygon"
## [37] "superpose.symbol"

Hence, modifications of some of these parameters will modify the graphical display of an ADEg object. For instance, margins are defined using layout.widths and layout.heights parameters, clip parameter allows to overpass panel boundaries and axis.line and axis.text allow to customize lines and text of axes.

d <- scale(olympic$tab)
g11 <- table.image(d, plot = FALSE)
g12 <- table.image(d, axis.line = list(col = "blue"), axis.text = list(col = "red"), 
  plot = FALSE)
ADEgS(c(g11, g12), layout = c(1, 2))

Parameters in adeg.par

The adeg.par slot is a list of graphical parameters specific to the adegraphics package. The name of parameters and their default value are available using the adegpar function which is inspired by the par function of the graphics package.

names(adegpar())

##  [1] "p1d"         "parrows"     "paxes"       "pbackground" "pellipses"  
##  [6] "pgrid"       "plabels"     "plegend"     "plines"      "pnb"        
## [11] "porigin"     "ppalette"    "ppoints"     "ppolygons"   "pSp"        
## [16] "psub"        "ptable"

A description of these parameters is available in the help page of the function (?adegpar). Note that each adeg.par parameter starts by the letter ’p’ and its name relates to the type of graphical element considered (ptable is for tables display, ppoints for points, parrows for arrows, etc). Each element of this list can contain one or more sublists. Details on a sublist are obtained using its name either as a parameter of the adegpar function or after the $ symbol. For example, if we want to know the different parameters to manage the display of points:

adegpar("ppoints")

## $ppoints
## $ppoints$alpha
## [1] 1
## 
## $ppoints$cex
## [1] 1
## 
## $ppoints$col
## [1] "black"
## 
## $ppoints$pch
## [1] 20
## 
## $ppoints$fill
## [1] "black"

adegpar()$ppoints

## $alpha
## [1] 1
## 
## $cex
## [1] 1
## 
## $col
## [1] "black"
## 
## $pch
## [1] 20
## 
## $fill
## [1] "black"

The full list of available parameters is summarized in Figure 3.

The ordinate represents the different sublists and the abscissa gives the name of the parameters available in each sublist. Note that some row names have two keys separated by a dot: the first key indicates the first level of the sublist, etc. For example plabels.boxes is the sublist boxes of the sublist plabels. The parameters border,col, alpha, lwd, lty and draw in plabels.boxes allow to control the aspect of the boxes around labels.

According to the function called, only some of the full list of adeg.par parameters are useful to modify the graphical display. Figure 4 indicates which parameters can affect the display of an object created by a given user function. For example, the background (pbackground parameter) can be modified for all functions whereas the display of ellipses (pellipses parameter) affects only three functions.

oldadegpar <- adegpar()
adegpar("plabels")

## $plabels
## $plabels$alpha
## [1] 1
## 
## $plabels$cex
## [1] 1
## 
## $plabels$col
## [1] "black"
## 
## $plabels$srt
## [1] "horizontal"
## 
## $plabels$optim
## [1] FALSE
## 
## $plabels$boxes
## $plabels$boxes$alpha
## [1] 1
## 
## $plabels$boxes$border
## [1] "black"
## 
## $plabels$boxes$col
## [1] "white"
## 
## $plabels$boxes$draw
## [1] TRUE
## 
## $plabels$boxes$lwd
## [1] 1
## 
## $plabels$boxes$lty
## [1] 1

g13 <- s.label(dfxy = pca1$li, plot = FALSE)
adegpar(plabels = list(col = "blue", cex = 1.5), paxes.draw = TRUE)
adegpar("plabels")

## $plabels
## $plabels$alpha
## [1] 1
## 
## $plabels$cex
## [1] 1.5
## 
## $plabels$col
## [1] "blue"
## 
## $plabels$srt
## [1] "horizontal"
## 
## $plabels$optim
## [1] FALSE
## 
## $plabels$boxes
## $plabels$boxes$alpha
## [1] 1
## 
## $plabels$boxes$border
## [1] "black"
## 
## $plabels$boxes$col
## [1] "white"
## 
## $plabels$boxes$draw
## [1] TRUE
## 
## $plabels$boxes$lwd
## [1] 1
## 
## $plabels$boxes$lty
## [1] 1

g14 <- s.label(dfxy = pca1$li, plot = FALSE)
ADEgS(c(g13, g14), layout = c(1, 2))

adegpar(oldadegpar)

adegpar("ppoints")

## $ppoints
## $ppoints$alpha
## [1] 1
## 
## $ppoints$cex
## [1] 1
## 
## $ppoints$col
## [1] "black"
## 
## $ppoints$pch
## [1] 20
## 
## $ppoints$fill
## [1] "black"

s.label(dfxy = pca1$li, plabels.cex = 0, ppoints = list(col = c(2, 4, 5), cex = 1.5, pch = 15))

adegpar("ppoints")

## $ppoints
## $ppoints$alpha
## [1] 1
## 
## $ppoints$cex
## [1] 1
## 
## $ppoints$col
## [1] "black"
## 
## $ppoints$pch
## [1] 20
## 
## $ppoints$fill
## [1] "black"

Parameters in g.args

The g.args slot is a list of parameters specific to the function used (and thus to the class of the returned object). Several parameters are very general and used in all adegraphics functions:

• xlim, ylim: limits of the graph on the x and y axes

• main, sub: main title and subtitle

• xlab, ylab: labels of the x and y axes

• scales: a list determining how the x and y axes (tick marks dans labels) are drawn; this is the scales parameter of the xyplot function of lattice

The ADEg.S2 objects can also contain spatial information (map stored as a Spatial object or neighborhood stored as a nb object):

• Sp, sp.layout: objects from the sp package to display spatial objects, Sp for maps and sp.layout for spatial widgets as a North arrow, scale, etc.

• nbobject: object of class nb or listw to display neighbor graphs.

When the facets (see the Partitioning the data (facets) section) argument is used, users can modify the parameter samelimits: if it is TRUE, all graphs have the same limits whereas limits are computed for each subgraph independently when it is FALSE. For example, considering the jv73 data set, each subgraph is computed with its own limits and labels are then more scattered:

s.label(pca2$li, facets = jv73$fac.riv, samelimits = FALSE)

Several other g.args parameters can be updated according to the class of the created object (see Figure 2).

Parameters applied on a ADEgS

Users can either apply the changes to all graphs or to update only one graph. Of an ADEgS, to apply changes on all the graphs contained in an ADEgS, the syntax is similar to the one described for an ADEg object. For example, background color can be changed for all graphs in g10 using the pbackground.col parameter.

g15 <- plot(coi1, pbackground.col = "steelblue")

To change the parameters of a given graph, the name of the parameter must be preceded by the name of the subgraph. This supposes that the names of subgraphs are known. For example, to modify only two graphs:

names(g15)

## [1] "Xax"       "Yax"       "eig"       "XYmatch"   "Yloadings" "Xloadings"

plot(coi1, XYmatch.pbackground.col = "steelblue",  XYmatch.pgrid.col = "red", 
     eig.ppolygons.col = "orange")

Labels customization

data(meaudret)
g16 <- s.label(pca3$li, plot = FALSE)
g17 <- s.label(pca3$li, ppoints.col= "red", plabels = list(box = list(draw = FALSE), 
  optim = TRUE), plot = FALSE)
ADEgS(c(g16, g17), layout = c(1, 2))

Ellipses, stars and convex hulls

g18 <- s.class(pca3$li, fac = meaudret$design$season, plot = FALSE)
g19 <- s.class(pca3$li, fac = meaudret$design$season, ellipseSize = 0, 
  chullSize = 1, starSize = 0.5, col = TRUE, plot = FALSE)
g20 <- s.class(pca3$li, fac = meaudret$design$season, pellipses.lwd = 2, 
  pellipses.border = 2:5, pellipses.col = 2:5, plot = FALSE)
g21 <- s.class(pca3$li, fac = meaudret$design$season, ellipseSize = 0, 
  chullSize = 0, ppolygons.lwd = 2, plines.col = 2:5, starSize = 1.2, plot = FALSE)
ADEgS(c(g18, g19, g20, g21), layout = c(2, 2))

Values and legend

data(rpjdl)
coa2 <- dudi.coa(rpjdl$fau, scannf = FALSE, nf = 3)
g22 <- s.value(coa2$li, coa2$li[,3], plot = FALSE)
g23 <- s.value(coa2$li, coa2$li[,3], method = "color", ppoints.cex = 0.8, 
  plegend.size= 0.8, plot = FALSE)
g24 <- s.value(coa2$li, coa2$li[,3], plegend.size = 0.8, ppoints.cex = 0.8, 
  symbol = "square", method = "color", key = list(columns = 1), 
  col = colorRampPalette(c("yellow", "blue"))(6), plot = FALSE)
g25 <- s.value(coa2$li, coa2$li[, 3], center = 0, method = "size", ppoints.cex = 0.6, 
  symbol = "circle", col = c("yellow", "red"), plot = FALSE)
ADEgS(c(g22, g23, g24, g25), layout = c(2, 2))

1-D plot

score1 <- c(rnorm(1000, mean = -0.5, sd = 0.5), rnorm(1000, mean = 1))
fac1 <- rep(c("A", "B"), each = 1000)
g26 <- s1d.density(score1, fac1, pback.col = "grey75", plot = FALSE)
g27 <- s1d.density(score1, fac1, col = c(2, 4), plot = FALSE)
g28 <- s1d.density(score1, fac1, col = c(2, 4), p1d.reverse = TRUE, p1d.horizontal = FALSE, 
  p1d.rug.draw = FALSE, plot = FALSE)
g29 <- s1d.density(score1, fac1, col = c(2, 4), ppolygons.alpha = 0.2, 
  p1d = list(rug = list(tck = 1, line = FALSE)), plot = FALSE)
ADEgS(c(g26, g27, g28, g29), layout = c(2, 2))

Maps and neighbor graphs

if(require(Guerry)) {
  library(sp)
  data(gfrance85)
  region.names <- data.frame(gfrance85)[, 5]
  col.region <- colors()[c(149, 254, 468, 552, 26)]
  g30 <- s.class(coordinates(gfrance85), region.names, porigin.include = FALSE, plot = FALSE)
  g31 <- s.class(coordinates(gfrance85), region.names, ellipseSize = 0, starSize = 0,
                 Sp = gfrance85, pgrid.draw = FALSE, pSp.col = col.region[region.names], pSp.alpha = 0.4,
                 plot = FALSE)
  ADEgS(c(g30, g31), layout = c(1, 2))
}

## Loading required package: Guerry

# if(require(Guerry)) {
#   s.Spatial(gfrance85[,7:12])
# }

data(mafragh, package = "ade4")
g32 <- s.label(mafragh$xy, nb = mafragh$nb, plot = FALSE)
g33 <- s.label(mafragh$xy, nb = mafragh$nb, pnb.ed.col = "red", plab.cex = 0, 
  pnb.node = list(cex = 3, col = "blue"), ppoints.col = "green", plot = FALSE)
ADEgS(c(g32, g33), layout = c(1, 2))

Ternary plots

data(euro123, package = "ade4")
df <- rbind.data.frame(euro123$in78, euro123$in86, euro123$in97)
row.names(df) <- paste(row.names(euro123$in78), rep(c(1, 2, 3), rep(12, 3)), sep = "")
g34 <- triangle.label(df, label = row.names(df), showposition = TRUE, plot = FALSE)
g35 <- triangle.label(euro123$in78, plabels.cex = 0, ppoints.cex = 2, addmean = TRUE, 
  show = FALSE, plot = FALSE)
ADEgS(c(g34, g35), layout = c(1, 2))