R Under development (unstable) (2023-10-09 r85295 ucrt) -- "Unsuffered Consequences"
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> ## delete/remove this file when 'scatter' functions will be removed in ade4
> 
> library(adegraphics)
The legacy packages maptools, rgdal, and rgeos, underpinning the sp package,
which was just loaded, were retired in October 2023.
Please refer to R-spatial evolution reports for details, especially
https://r-spatial.org/r/2023/05/15/evolution4.html.
It may be desirable to make the sf package available;
package maintainers should consider adding sf to Suggests:.
Registered S3 methods overwritten by 'adegraphics':
  method         from
  biplot.dudi    ade4
  kplot.foucart  ade4
  kplot.mcoa     ade4
  kplot.mfa      ade4
  kplot.pta      ade4
  kplot.sepan    ade4
  kplot.statis   ade4
  scatter.coa    ade4
  scatter.dudi   ade4
  scatter.nipals ade4
  scatter.pco    ade4
  score.acm      ade4
  score.mix      ade4
  score.pca      ade4
  screeplot.dudi ade4
> pdf("ade4-functions.pdf")
> 
> ##################### scatter.dudi
> data(deug, package = "ade4")
> dd1 <- ade4::dudi.pca(deug$tab, scannf = FALSE, nf = 4)
> scatter(dd1, posieig = "bottomright")
> scatter(dd1, posieig = "bottomright", plot = T, prop = TRUE)
> scatter(dd1, posieig = "none", plot = T)
> scatter(dd1, posieig = "bottomleft", plot = T)
> scatter(dd1, posieig = "topright", plot = T)
> scatter(dd1, posieig = "topleft", plot = T, eig.col = c("white", "blue", "red"))
> 
> data(rhone, package = "ade4")
> dd1 <- ade4::dudi.pca(rhone$tab, nf = 4, scannf = FALSE)
> g1 <- scatter(dd1, sub = "Principal component analysis", row = list(plabels.optim = TRUE), col.pla.boxes.alpha = 0.5)
> g1[2, drop = TRUE]
> scatter(dd1, row = list(sub = "Principal component analysis", plabels.optim = TRUE), col.pla.boxes.alpha = 0.5)
> scatter(dd1, prop = TRUE, ppoints.cex = 0.2, density.plot = TRUE, row = list(threshold = 0.01))
> 
> scatter(dd1, posieig = "none")
> scatter(dd1, posieig = "bottomright")
> scatter(dd1, posieig = c(0.5, 0.5))
> scatter(dd1, posieig = c(0.5, 0.5, 1, 1))
> 
> 
> ##################### scatter.coa
> data(housetasks, package = "ade4")
> par(mfrow = c(2, 2))
> dd2 <- ade4::dudi.coa(housetasks, scan = FALSE)
> ade4::scatter(dd2, method = 1, sub = "1 / Standard", posieig = "none")
> ade4::scatter(dd2, method = 2, sub = "2 / Columns -> averaging -> Rows", posieig = "none")
> ade4::scatter(dd2, method = 3, sub = "3 / Rows -> averaging -> Columns ", posieig = "none")
> par(mfrow = c(1, 1))
> 
> g1 <- scatter(dd2, method = 1, row.sub = "1 / Standard", posieig = "none", plot = FALSE)
> g2 <- scatter(dd2, method = 2, col.sub = "2 / Columns -> averaging -> Rows", posieig = "none", plot = FALSE)
> g3 <- scatter(dd2, method = 3, row.sub = "3 / Rows -> averaging -> Columns ", posieig = "none", plot = FALSE)
> G <- ADEgS(list(g1, g2, g3), layout = c(2, 2), plot = TRUE)
> 
> scatter(dd2, posieig = "none")
> scatter(dd2, posieig = "bottomright")
> scatter(dd2, posieig = c(0.5, 0.5))
> scatter(dd2, posieig = c(0.5, 0.5, 1, 1))
> 
> 
> ##################### scatter.pco
> data(yanomama, package = "ade4")
> gen <- ade4::quasieuclid(as.dist(yanomama$gen))
> gen1 <- ade4::dudi.pco(gen, scann = FALSE, nf = 3)
> scatter(gen1, posieig = "none")
> scatter(gen1, posieig = "bottomri")
> scatter(gen1, posieig = c(0.5, 0.5))
> scatter(gen1, posieig = c(0.5, 0.5, 1, 1))
> 
> 
> ##################### scatter.nipals
> data(doubs, package = "ade4")
> acp1 <- ade4::dudi.pca(doubs$env, scannf = FALSE, nf = 2)
> nip1 <- ade4::nipals(doubs$env)
> scatter(nip1, posieig = "none")
> scatter(nip1, posieig = "bottomri")
> scatter(nip1, posieig = c(0.5, 0.5))
> scatter(nip1, posieig = c(0.5, 0.5, 1, 1))
> 
> 
> ##################### score.inertia - plot.inertia
> data(housetasks, package = "ade4")
> coa2 <- ade4::dudi.coa(housetasks, scann = FALSE)
> res21 <- ade4::inertia(coa2, row = TRUE, col = FALSE)
> plot(res21, posieig = "none")
> plot(res21, posieig = "bottomri")
> plot(res21, posieig = c(0.5,0.5))
> plot(res21, posieig = c(0.5, 0.5, 1, 1))
> score(res21, posieig = "none")
> score(res21, posieig = "bottomri")
> score(res21, posieig = c(0.5, 0.5))
> score(res21, posieig = c(0.5, 0.5, 1, 1))
> 
> res22 <- ade4::inertia(coa2, row = FALSE, col = TRUE)
> plot(res22, posieig = "none")
> plot(res22, posieig = "bottomri")
> plot(res22, posieig = c(0.5, 0.5))
> plot(res22, posieig = c(0.5, 0.5, 1, 1))
> score(res22, posieig = "none")
> score(res22, posieig = "bottomri")
> score(res22, posieig = c(0.5, 0.5))
> score(res22, posieig = c(0.5, 0.5, 1, 1))
> 
> res23 <- ade4::inertia(coa2, row = TRUE, col = TRUE)
> plot(res23, posieig = "none")
> plot(res23, posieig = "bottomri")
> plot(res23, posieig = c(0.5, 0.5))
> plot(res23, posieig = c(0.5, 0.5, 1, 1))
> score(res23, posieig = "none")
> score(res23, posieig = "bottomri")
> score(res23, posieig = c(0.5, 0.5))
> score(res23, posieig = c(0.5, 0.5, 2, 2))
> 
> 
> ##################### plot.acm
> data(lascaux, package = "ade4")
> 
> acm1 <- ade4::dudi.acm(lascaux$ornem, sca = FALSE)
> p1 <- proc.time()
> ade4::scatter(acm1)
> Tade4 <- proc.time() - p1
> 
> p2 <- proc.time()
> plot(acm1, ppoints.cex = 0.3, plot = T)
> Tadegraphics <- proc.time() - p2
> ## faster calculus, longest display than for ade4
> 
> 
> ##################### plot.fca
> data(coleo, package = "ade4")
> coleo.fuzzy <- ade4::prep.fuzzy.var(coleo$tab, coleo$col.blocks)
2 missing data found in block 1 
1 missing data found in block 3 
2 missing data found in block 4 
> 
> fca1 <- ade4::dudi.fca(coleo.fuzzy, scannf = FALSE, nf = 3)
> ade4::scatter(fca1)
> plot(fca1)
> 
> proc.time()
   user  system elapsed 
  15.26    0.21   15.46