+ n = 900
+ x = seq(0,9.5,0.1)
+ L = length(x) #96 1/4h
+ K1 = 60
+ s = lapply( seq_len(K1), function(i) x^(1+i/30)*cos(x+i) )
+ series = matrix(nrow=L, ncol=n)
+ for (i in seq_len(n))
+ series[,i] = s[[I(i,K1)]] + rnorm(L,sd=0.01)
+ getSeries = function(indices) {
+ indices = indices[indices <= n]
+ if (length(indices)>0) series[,indices] else NULL
+ }
+ wf = "haar"
+ ctype = "absolute"
+ getContribs = function(indices) curvesToContribs(series[,indices],wf,ctype)
+ require("cluster", quietly=TRUE)
+ browser()
+ algoClust1 = function(contribs,K) cluster::pam(contribs,K,diss=FALSE)$id.med
+ indices1 = clusteringTask1(1:n, getContribs, K1, algoClust1, 75, verbose=TRUE, parll=FALSE)
+ medoids_K1 = getSeries(indices1)