Get paired individual on a Coe, PCA or LDA objects

If you have paired individuals, i.e. before and after a treatment or for repeated measures, and if you have coded coded it into $fac, this methods allows you to retrieve the corresponding PC/LD scores, or coefficients for Coe objects.

Usage

get_pairs(x, fac, range)

Arguments

x

any Coe, PCA of LDA object.

fac

factor or column name or id corresponding to the pairing factor.

range

numeric the range of coefficients for Coe, or PC (LD) axes on which to return scores.

Value

a list with components x1 all coefficients/scores corresponding to the first level of the fac provided; x2 same thing for the second level; fac the corresponding fac.

Examples

bot2 <- bot1 <- coo_scale(coo_center(coo_sample(bot, 60)))
bot1$fac$session <- factor(rep("session1", 40))
# we simulate an measurement error
bot2 <- coo_jitter(bot1, amount=0.01)
bot2$fac$session <- factor(rep("session2", 40))
botc <- combine(bot1, bot2)
botcf <- efourier(botc, 12)
#> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details

# we gonna plot the PCA with the two measurement sessions and the two types
botcp <- PCA(botcf)
plot(botcp, "type", col=col_summer(2), pch=rep(c(1, 20), each=40), eigen=FALSE)
#> will be deprecated soon, see ?plot_PCA
bot.pairs <- get_pairs(botcp, fac = "session", range=1:2)
segments(bot.pairs$session1[, 1], bot.pairs$session1[, 2],
       bot.pairs$session2[, 1], bot.pairs$session2[, 2],
       col=col_summer(2)[bot.pairs$fac$type])