library(SensoMineR)
#Importation
classique <- read.table("Experts.csv", header=TRUE, sep=";", na.strings="", dec=",")
for(i in 1:3) classique[,i]<-as.factor(classique[,i])

#ACP
classique.PCA<-classique[, c("IntensiteCouleur", "IntensiteOlfactive", "IntensiteDAttaque", "Sucre", "Acide", "Amer", "AromeOrange", 
"AromeBanane","AromeMangue", "AromeCitron", "PersistanceGout", "Pulpeux", "Epaisseur")]
res<-PCA(classique.PCA , scale.unit=TRUE, ncp=5, graph = FALSE)

plot.PCA(res, axes=c(1, 2), choix="ind", habillage="none", col.ind="black", col.ind.sup="blue", col.quali="magenta", label=c("ind", "ind.sup", "quali"))
plot.PCA(res, axes=c(1, 2), choix="var", col.var="black", col.quanti.sup="blue", label=c("var", "quanti.sup"), lim.cos2.var=0)
remove(classique.PCA)

#PANELIPSE
results=panellipse(classique[,c("Juge", "Produit", "IntensiteCouleur", "IntensiteOlfactive","IntensiteDAttaque", "Sucre", "Acide", "Amer", "AromeOrange", "AromeBanane", "AromeMangue", "AromeCitron", "PersistanceGout", "Pulpeux", "Epaisseur")],
col.p=2,col.j=1,firstvar=3,alpha=0.05,coord = c(1,2), nbsimul =500,nbchoix =NULL,level.search.desc=0.2,scale.unit=1,variability.variable =TRUE,
centerbypanelist =TRUE,scalebypanelist=FALSE,name.panelist=FALSE)


#PREFMAP
pref_classique <- read.table("prefmap_classique.csv", header=TRUE, sep=";", na.strings="", dec=",",row.names=1)
prefclassique=carto(pref_classique[,1:2],pref_classique[,-c(1:2)], regmod=1,coord = c(1,2), resolution =200,level =0,nb.clusters=0,label.j=FALSE)