pkg/tests/testthat/test-computeMu.R

   1 test_that("on input of sufficient size, β/||β|| is estimated accurately enough",
   2 {
   3   n <- 100000
   4   d <- 2
   5   K <- 2
   6   p <- 1/2
   7
   8   βs_ref <- array( c(1,0,0,1 , 1,-2,3,1), dim=c(d,K,2) )
   9   for (i in 1:(dim(βs_ref)[3]))
  10   {
  11     μ_ref <- normalize(βs_ref[,,i])
  12     for (link in c("logit","probit"))
  13     {
  14       cat("\n\n",link," :\n",sep="")
  15
  16       io <- generateSampleIO(n, p, βs_ref[,,i], rep(0,K), link)
  17       μ <- computeMu(io$X, io$Y, list(K=K))
  18       μ_aligned <- alignMatrices(list(μ), ref=μ_ref, ls_mode="exact")[[1]]
  19
  20       #Some traces: 0 is not well estimated, but others are OK
  21       cat("Reference normalized matrix:\n")
  22       print(μ_ref)
  23       cat("Estimated normalized matrix:\n")
  24       print(μ_aligned)
  25       cat("Difference norm (Matrix norm ||.||_1, max. abs. sum on a column)\n")
  26       diff_norm <- norm(μ_ref - μ_aligned)
  27       cat(diff_norm,"\n")
  28
  29       # NOTE: 0.5 is loose threshold, but values around 0.3 are expected...
  30       expect_lt( diff_norm, 0.5 )
  31     }
  32   }
  33 })