# NOT RUN {
library("fda")
data("runs", package = "trackeR")
dp <- distributionProfile(runs, what = "speed")
dpFun <- profile2fd(dp, what = "speed",
fdnames = list("speed", "sessions", "time above threshold"))
dp.pca <- pca.fd(dpFun, nharm = 4)
## 1st harmonic captures vast majority of the variation
dp.pca$varprop
## time spent above speed = 0 is the characteristic distinguishing the profiles
plot(dp.pca, harm = 1)
sumRuns <- summary(runs)
plot(sumRuns$durationMoving, dp.pca$scores[,1])
# }
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