epclust/R/algorithms.R

   1 #NOTE: always keep ID in first column
   2 curvesToCoeffs = function(series, wf)
   3 {
   4     library(wavelets)
   5     L = length(series[1,])
   6     D = ceiling( log(L-1) )
   7     nb_sample_points = 2^D
   8     #TODO: parallel::parApply() ?!
   9     res = apply(series, 1, function(x) {
  10         interpolated_curve = spline(1:(L-1), x[2:L], n=nb_sample_points)$y
  11         W = wavelets::dwt(interpolated_curve, filter=wf, D)@W
  12         nrj_coeffs = rev( sapply( W, function(v) ( sqrt( sum(v^2) ) ) ) )
  13         return ( c(x[1], nrj_coeffs) )
  14     })
  15     return (as.data.frame(res))
  16 }
  17
  18 getClusters = function(data, K)
  19 {
  20     library(cluster)
  21     pam_output = cluster::pam(data, K)
  22     return ( list( clusts=pam_output$clustering, medoids=pam_output$medoids,
  23         ranks=pam_output$id.med ) )
  24 }