epclust/tests/testthat/test.computeMedoidsIndices.R

   1 context("computeMedoidsIndices")
   2
   3 test_that("computeMedoidsIndices behave as expected",
   4 {
   5     # Generate a gaussian mixture
   6     n = 999
   7     L = 7
   8     medoids = cbind( rep(0,L), rep(-5,L), rep(5,L) )
   9     # short series...
  10     series = t( rbind( MASS::mvrnorm(n/3, medoids[,1], diag(L)),
  11         MASS::mvrnorm(n/3, medoids[,2], diag(L)),
  12         MASS::mvrnorm(n/3, medoids[,3], diag(L)) ) )
  13
  14     # With high probability, medoids indices should resemble 1,1,1,...,2,2,2,...,3,3,3,...
  15     require("bigmemory", quietly=TRUE)
  16     mi = epclust:::computeMedoidsIndices(bigmemory::as.big.matrix(medoids)@address, series)
  17     mi_ref = rep(1:3, each=n/3)
  18     expect_lt( mean(mi != mi_ref), 0.01 )
  19
  20     # Now with a random matrix, compare with (trusted) R version
  21     series = matrix(runif(n*L, min=-7, max=7), nrow=L)
  22     mi = epclust:::computeMedoidsIndices(bigmemory::as.big.matrix(medoids)@address, series)
  23     mi_ref = R_computeMedoidsIndices(medoids, series)
  24     expect_equal(mi, mi_ref)
  25 })