4.3. Individual Wine Configurations
res.LexCA.Fr.list <- lapply(1:length(res.TD.Fr.list), function(i) LexCA(res.TD.Fr.list[[i]], graph=FALSE))
Representation for one of the judges, in this case the Catalan judge CE10.
Two possibilities:
1. Doing one CA only with CE10 from the original data baseCat.
res.TD.JCE10 <- TextData(baseCat,var.text="CE10", Fmin=1, stop.word.user=str.Cat.stopworduser)
res.LexCA.JCE10 <- LexCA(res.TD.JCE10, graph=FALSE)
2. Extracting the CE10 judge from the TextData object into the TextData list. CE10 has the position 8.
names(baseCat)
|
1 |
"CE1" "CE2" "CE3" "CE4" "CE7" "CE8" "CE9" "CE10" "CE11" |
res.TD.Cat.list[[8]] # Accessing by judge’s number
res.TD.Cat.list[[“CE10”]] # Accessing by judge’s name
To plot the results, we can use the plot by default (there are 12 unlabeled data points):
pJCE10 <- plot(res.LexCA.JCE10,col.doc="grey30",col.word="black",cex=0.8,title=" ",autoLab=c("yes"), graph.type = c("ggplot"))
pJCE10
|
1 2 |
Warning: ggrepel: 12 unlabeled data points (too many overlaps). Consider increasing max.overlaps |
To built the first factorial plane translating the words to English, we need some steps.
Building a data frame reading the coordinates names of the wines:
Dim.x <- 1
Dim.y <- 2
df.1.wines <- data.frame(res.LexCA.JCE10$row$coord[,Dim.x] ,res.LexCA.JCE10$row$coord[,Dim.y], rownames(res.LexCA.JCE10$row$coord))[,c(Dim.x,Dim.y)]
colnames(df.1.wines) <- c("x","y")
df.1.wines
|
1 2 3 4 5 6 7 8 9 |
x y PG05 0.000000e+00 -1.311567e-15 PG06 -1.312570e+00 2.754061e+00 EG05 -3.631635e-01 -7.875589e-01 EG06 -3.631635e-01 -7.875589e-01 PC05 2.946806e+00 7.899539e-01 PC06 3.006498e-16 -4.509747e-16 EC05 -3.631635e-01 -7.875589e-01 EC06 3.006498e-16 -4.509747e-16 |
Reading the words, translating to English and adding to the coordinates of the words:
df.1.words <- data.frame(res.LexCA.JCE10$col$coord[,Dim.x] ,res.LexCA.JCE10$col$coord[,Dim.y], rownames(res.LexCA.JCE10$col$coord))[,c(Dim.x, Dim.y)]
colnames(df.1.words) <- c("x","y")
df.1.words
|
1 2 3 4 5 6 7 8 9 10 11 |
x y brisa -1.312570e+00 2.754061e+00 cítric -3.631635e-01 -7.875589e-01 desequilibri 2.946806e+00 7.899539e-01 floral 2.946806e+00 7.899539e-01 fruitsec -3.631635e-01 -7.875589e-01 fum 3.758123e-17 7.516245e-17 rodó -3.631635e-01 -7.875589e-01 roure 3.758123e-17 7.516245e-17 tànnic 3.758123e-17 7.516245e-17 vegetal -1.312570e+00 2.754061e+00 |
words.Fig1 <-rownames(df.1.words)
words.Fig1[words.Fig1 == "brisa"] <- "breeze"
words.Fig1[words.Fig1 == "cítric"] <- "citrus"
words.Fig1[words.Fig1 == "desequilibri"] <- "unbalanced"
words.Fig1[words.Fig1 == "floral"] <- "floral"
words.Fig1[words.Fig1 == "fruitsec"] <- "driedfruit"
words.Fig1[words.Fig1 == "fum"] <- "smoky"
words.Fig1[words.Fig1 == "rodó"] <- "round"
words.Fig1[words.Fig1 == "roure"] <- "oak"
words.Fig1[words.Fig1 == "tànnic"] <- "tannic"
words.Fig1[words.Fig1 == "vegetal"] <- "vegetal"
words.Fig1
|
1 2 |
"breeze" "citrus" "unbalanced" "floral" "driedfruit" "smoky" "round" "oak" "tannic" "vegetal" |
rownames(df.1.words) <- words.Fig1
The coordinates of the wines and the words in English are joined together
dfWW <- rbind(df.1.wines,df.1.words)
dfWW
|
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 |
x y PG05 0.000000e+00 -1.311567e-15 PG06 -1.312570e+00 2.754061e+00 EG05 -3.631635e-01 -7.875589e-01 EG06 -3.631635e-01 -7.875589e-01 PC05 2.946806e+00 7.899539e-01 PC06 3.006498e-16 -4.509747e-16 EC05 -3.631635e-01 -7.875589e-01 EC06 3.006498e-16 -4.509747e-16 breeze -1.312570e+00 2.754061e+00 citrus -3.631635e-01 -7.875589e-01 unbalanced 2.946806e+00 7.899539e-01 floral 2.946806e+00 7.899539e-01 driedfruit -3.631635e-01 -7.875589e-01 smoky 3.758123e-17 7.516245e-17 round -3.631635e-01 -7.875589e-01 oak 3.758123e-17 7.516245e-17 tannic 3.758123e-17 7.516245e-17 vegetal -1.312570e+00 2.754061e+00 |
First, we plot the LexCA drawing without words or wines using ggrepel library to separate words and wines placed very close to each other:
library(ggrepel)
pJCE10 <-plot(res.LexCA.JCE10,col.doc="white",col.word="white",cex=0.0,title=" ",autoLab=c("no"), graph.type = c("ggplot"))
pJCE10
To add the rest of the elements in a black and white figure:
new.xlab <- paste0("Dim 1 (", round(res.LexCA.JCE10$eig[Dim.x,2],1), "%)")
new.ylab <- paste0("Dim 2 (", round(res.LexCA.JCE10$eig[Dim.y,2],1), "%)")
set.seed(9123)
Figure1 <- pJCE10 + theme_light() + xlab(new.xlab)+ ylab(new.ylab) +
theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank())+
geom_hline(yintercept=0, linetype="dashed", color = "grey")+
geom_vline(xintercept=0, linetype="dashed", color = "grey")+
geom_text_repel(aes(x=dfWW[,Dim.x] , y=dfWW[,Dim.y], label = rownames(dfWW)), max.overlaps=100,
size=7, fontface = "bold") +
theme(axis.title.x= element_text(size=17, face="bold"))+
theme(axis.title.x = element_text(vjust = -2, hjust=0.5))+
theme(axis.title.y= element_text(size=17, face="bold"))+
theme(plot.margin = grid::unit(c(t=0,r= 2,b=5, l=2), "mm"))+
theme(panel.border = element_rect(colour = "black", fill=NA, linewidth=1))+
theme(axis.text.x = element_text(size=rel(1.6)))+
theme(axis.text.y = element_text(size=rel(1.6)))
set.seed(9123)
Figure1
Adding different colors for the 8 wines (in red) and 10 words (in blue)
cols.Fig1 <- c(rep("#CC0000", 8), rep("blue", 10))
set.seed(9123)
Figure1 <- pJCE10 + theme_light() + xlab(new.xlab)+ ylab(new.ylab) +
theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank())+
geom_hline(yintercept=0, linetype="dashed", color = "grey")+
geom_vline(xintercept=0, linetype="dashed", color = "grey")+
geom_text_repel(aes(x=dfWW[,Dim.x] , y=dfWW[,Dim.y], label = rownames(dfWW)), max.overlaps=50,
size=7, fontface = "bold", colour=cols.Fig1) +
theme(axis.title.x= element_text(size=17, face="bold"))+
theme(axis.title.x = element_text(vjust = -2, hjust=0.5))+
theme(axis.title.y= element_text(size=17, face="bold"))+
theme(plot.margin = grid::unit(c(t=0,r= 2,b=5, l=2), "mm"))+
theme(panel.border = element_rect(colour = "black", fill=NA, linewidth=1))+
theme(axis.text.x = element_text(size=rel(1.6)))+
theme(axis.text.y = element_text(size=rel(1.6)))+
ggtitle("Figure 1. Individual configuration as provided by judge CE10")
set.seed(9123)
Figure1
If we want to print Figure 1 to pdf file:
graphics.off()
X11 ()
set.seed(9123)
plot (Figure1)
dev.print(pdf, 'Figure1.pdf')
dev.off ()
If we want to print Figure 1 to svg file: