X-Git-Url: https://git.auder.net/?a=blobdiff_plain;f=epclust%2FR%2Falgorithms.R;fp=epclust%2FR%2Falgorithms.R;h=0000000000000000000000000000000000000000;hb=5c6529795907ba1b34d4552cbfd0e0cbb77cac0f;hp=97dce901d54c3dce05f6ebb834c675fd121266d3;hpb=db6fc17ddd53fb0c64cf957296dc615ba830db56;p=epclust.git

diff --git a/epclust/R/algorithms.R b/epclust/R/algorithms.R
deleted file mode 100644
index 97dce90..0000000
--- a/epclust/R/algorithms.R
+++ /dev/null
@@ -1,24 +0,0 @@
-#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 ) )
-}