epclust/tests/testthat/helper.clustering.R

   1 # Shorthand: map 1->1, 2->2, 3->3, 4->1, ..., 149->2, 150->3, ... (is base==3)
   2 I = function(i, base)
   3     (i-1) %% base + 1
   4
   5 # Compute the sum of (normalized) sum of squares of closest distances to a medoid.
   6 # Note: medoids can be a big.matrix
   7 computeDistortion = function(series, medoids)
   8 {
   9     if (bigmemory::is.big.matrix(medoids))
  10         medoids = medoids[,] #extract standard matrix
  11
  12     n = nrow(series) ; L = ncol(series)
  13     distortion = 0.
  14     for (i in seq_len(n))
  15         distortion = distortion + min( colSums( sweep(medoids,1,series[,i],'-')^2 ) / L )
  16
  17     distortion / n
  18 }