#NOTE: always keep ID in first column
curvesToCoeffs = function(series, wf)
{
	library(wavelets)
	L = length(series[1,])
	D = ceiling( log(L-1) )
	nb_sample_points = 2^D
	#TODO: parallel::parApply() ?!
	res = apply(series, 1, function(x) {
		interpolated_curve = spline(1:(L-1), x[2:L], n=nb_sample_points)$y
		W = wavelets::dwt(interpolated_curve, filter=wf, D)@W
		nrj_coeffs = rev( sapply( W, function(v) ( sqrt( sum(v^2) ) ) ) )
		return ( c(x[1], nrj_coeffs) )
	})
	return (as.data.frame(res))
}

getClusters = function(data, K)
{
	library(cluster)
	pam_output = cluster::pam(data, K)
	return ( list( clusts=pam_output$clustering, medoids=pam_output$medoids,
		ranks=pam_output$id.med ) )
}