pkg/tests/testthat/test.computeFilaments.R

   1 #TODO: toy dataset, check that indices returned are correct + colors
   2
   3 context("Check that getParamsDirs behaves as expected")
   4
   5 test_that("on input of sufficient size, beta is estimated accurately enough", {
   6     n = 100000
   7     d = 2
   8     K = 2
   9     Pr = c(0.5, 0.5)
  10
  11     betas_ref = array( c(1,0,0,1 , 1,-2,3,1), dim=c(2,2,2) )
  12     for (i in 1:(dim(betas_ref)[3]))
  13     {
  14         beta_ref = betas_ref[,,i]
  15         #all parameters are supposed to be of norm 1: thus, normalize beta_ref
  16         norm2 = sqrt(colSums(beta_ref^2))
  17         beta_ref = beta_ref / norm2[col(beta_ref)]
  18
  19         io = generateSampleIO(n, d, K, Pr, beta_ref)
  20         beta = getParamsDirs(io$X, io$Y, K)
  21         betas = .labelSwitchingAlign(
  22             array( c(beta_ref,beta), dim=c(d,K,2) ), compare_to="first", ls_mode="exact")
  23
  24         #Some traces: 0 is not well estimated, but others are OK
  25         cat("\n\nReference parameter matrix:\n")
  26         print(beta_ref)
  27         cat("Estimated parameter matrix:\n")
  28         print(betas[,,2])
  29         cat("Difference norm (Matrix norm ||.||_1, max. abs. sum on a column)\n")
  30         diff_norm = norm(beta_ref - betas[,,2])
  31         cat(diff_norm,"\n")
  32
  33         #NOTE: 0.5 is loose threshold, but values around 0.3 are expected...
  34         expect_that( diff_norm, is_less_than(0.5) )
  35     }
  36 })