pkg/tests/testthat/test-alignMatrices.R

   1 context("alignMatrices")
   2
   3 # Helper to generate a random series of matrices to align
   4 .generateMatrices = function(d, K, N, noise)
   5 {
   6   matrices = list( matrix(runif(d*K, min=-1, max=1),ncol=K) ) #reference
   7   for (i in 2:N)
   8   {
   9     matrices[[i]] <- matrices[[1]][,sample(1:K)]
  10     if (noise)
  11       matrices[[i]] = matrices[[i]] + matrix(rnorm(d*K, sd=0.05), ncol=K)
  12   }
  13   matrices
  14 }
  15
  16 test_that("labelSwitchingAlign correctly aligns de-noised parameters",
  17 {
  18   N = 30 #number of matrices
  19   d_K_list = list(c(2,2), c(5,3))
  20   for (i in 1:2)
  21   {
  22     d = d_K_list[[i]][1]
  23     K = d_K_list[[i]][2]
  24
  25     # 1] Generate matrix series
  26     matrices_permut = .generateMatrices(d,K,N,noise=FALSE)
  27
  28     # 2] Call align function with mode=approx1
  29     matrices_aligned =
  30       alignMatrices(matrices_permut[2:N], ref=matrices_permut[[1]], ls_mode="approx1")
  31
  32     # 3] Check alignment
  33     for (j in 2:N)
  34       expect_equal(matrices_aligned[[j-1]], matrices_permut[[1]])
  35
  36     # 2bis] Call align function with mode=approx2
  37     matrices_aligned =
  38       alignMatrices(matrices_permut[2:N], ref=matrices_permut[[1]], ls_mode="approx2")
  39
  40     # 3bis] Check alignment
  41     for (j in 2:N)
  42       expect_equal(matrices_aligned[[j-1]], matrices_permut[[1]])
  43   }
  44 })
  45
  46 test_that("labelSwitchingAlign correctly aligns noisy parameters",
  47 {
  48   N = 30 #number of matrices
  49   d_K_list = list(c(2,2), c(5,3))
  50   for (i in 1:2)
  51   {
  52     d = d_K_list[[i]][1]
  53     K = d_K_list[[i]][2]
  54     max_error = d * 0.2 #TODO: what value to choose ?
  55
  56     # 1] Generate matrix series
  57     matrices_permut = .generateMatrices(d,K,N,noise=TRUE)
  58
  59     # 2] Call align function
  60     matrices_aligned = alignMatrices(matrices_permut, ref="mean", ls_mode="exact")
  61
  62     # 3] Check alignment
  63     for (j in 2:N)
  64     {
  65       expect_that( norm(matrices_aligned[[j]] - matrices_permut[[1]]),
  66         is_less_than(max_error) )
  67     }
  68   }
  69 })