Package v.1.0 ready to be sent to CRAN

[morpheus.git] / pkg / tests / testthat / test-jointDiag.R

diff --git a/pkg/tests/testthat/test-jointDiag.R b/pkg/tests/testthat/test-jointDiag.R
index bb12a6c..619c9b6 100644 (file)
--- a/pkg/tests/testthat/test-jointDiag.R
+++ b/pkg/tests/testthat/test-jointDiag.R
@@ -3,27 +3,27 @@ context("jointDiag::ajd")
 #auxiliary to test diagonality
 .computeMuCheckDiag = function(X, Y, K, jd_method, β_ref)
 {
-  d = ncol(X)
+  d <- ncol(X)
   #TODO: redundant code, same as computeMu() main method. Comments are stripped
-  M3 = .Moments_M3(X,Y)
-  M2_t = array(dim=c(d,d,d))
+  M3 <- .Moments_M3(X,Y)
+  M2_t <- array(dim=c(d,d,d))
   for (i in 1:d)
   {
-    ρ = c(rep(0,i-1),1,rep(0,d-i))
-    M2_t[,,i] = .T_I_I_w(M3,ρ)
+    ρ <- c(rep(0,i-1),1,rep(0,d-i))
+    M2_t[,,i] <- .T_I_I_w(M3,ρ)
   }
-  jd = jointDiag::ajd(M2_t, method=jd_method)
-  V = if (jd_method=="uwedge") jd$B else solve(jd$A)
-  M2_t = array(dim=c(d,d,K))
+  jd <- jointDiag::ajd(M2_t, method=jd_method)
+  V <- if (jd_method=="uwedge") jd$B else solve(jd$A)
+  M2_t <- array(dim=c(d,d,K))
   for (i in 1:K)
-    M2_t[,,i] = .T_I_I_w(M3,V[,i])
+    M2_t[,,i] <- .T_I_I_w(M3,V[,i])
   #END of computeMu() code
 
-  max_error = 0.5 #TODO: tune ?
-  invβ = MASS::ginv(β_ref)
+  max_error <- 1.0 #TODO: tune ?
+  invβ <- MASS::ginv(β_ref)
   for (i in 1:K)
   {
-    shouldBeDiag = invβ %*% M2_t[,,i] %*% t(invβ)
+    shouldBeDiag <- invβ %*% M2_t[,,i] %*% t(invβ)
     expect_that(
       mean( abs(shouldBeDiag[upper.tri(shouldBeDiag) | lower.tri(shouldBeDiag)]) ),
       is_less_than(max_error) )
@@ -32,17 +32,17 @@ context("jointDiag::ajd")
 
 test_that("'jedi' and 'uwedge' joint-diagonalization methods return a correct matrix",
 {
-  n = 10000
-  d_K = list( c(2,2), c(5,3), c(20,13) )
+  n <- 10000
+  d_K <- list( c(2,2), c(5,3), c(20,13) )
 
   for (dk_index in 1:length(d_K))
   {
-    d = d_K[[dk_index]][1]
-    K = d_K[[dk_index]][2]
+    d <- d_K[[dk_index]][1]
+    K <- d_K[[dk_index]][2]
     #NOTE: sometimes large errors if pr is not balanced enough (e.g. random);
     #      same note for β. However we could be more random than that...
-    β_ref = rbind(diag(K),matrix(0,nrow=d-K,ncol=K))
-    io = generateSampleIO(n, p=rep(1/K,K-1), β=β_ref, rep(0,K), link="logit")
+    β_ref <- rbind(diag(K),matrix(0,nrow=d-K,ncol=K))
+    io <- generateSampleIO(n, p=rep(1/K,K-1), β=β_ref, rep(0,K), link="logit")
     .computeMuCheckDiag(io$X, io$Y, K, jd_method="uwedge", β_ref)
     #TODO: some issues with jedi method (singular system)
     #.computeMuCheckDiag(io$X, io$Y, K, jd_method="jedi", β_ref)