pkg/tests/testthat/test-computeMu.R

   1 context("computeMu")
   2
   3 test_that("on input of sufficient size, β/||β|| is estimated accurately enough",
   4 {
   5   n <- 100000
   6   d <- 2
   7   K <- 2
   8   p <- 1/2
   9
  10   βs_ref <- array( c(1,0,0,1 , 1,-2,3,1), dim=c(d,K,2) )
  11   for (i in 1:(dim(βs_ref)[3]))
  12   {
  13     μ_ref <- normalize(βs_ref[,,i])
  14     for (link in c("logit","probit"))
  15     {
  16       cat("\n\n",link," :\n",sep="")
  17
  18       io <- generateSampleIO(n, p, βs_ref[,,i], rep(0,K), link)
  19       μ <- computeMu(io$X, io$Y, list(K=K))
  20       μ_aligned <- alignMatrices(list(μ), ref=μ_ref, ls_mode="exact")[[1]]
  21
  22       #Some traces: 0 is not well estimated, but others are OK
  23       cat("Reference normalized matrix:\n")
  24       print(μ_ref)
  25       cat("Estimated normalized matrix:\n")
  26       print(μ_aligned)
  27       cat("Difference norm (Matrix norm ||.||_1, max. abs. sum on a column)\n")
  28       diff_norm <- norm(μ_ref - μ_aligned)
  29       cat(diff_norm,"\n")
  30
  31       #NOTE: 0.5 is loose threshold, but values around 0.3 are expected...
  32       expect_that( diff_norm, is_less_than(0.5) )
  33     }
  34   }
  35 })