Package v.1.0 ready to be sent to CRAN

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

diff --git a/pkg/tests/testthat/test-alignMatrices.R b/pkg/tests/testthat/test-alignMatrices.R
index 8ce7abf..47625b1 100644 (file)
--- a/pkg/tests/testthat/test-alignMatrices.R
+++ b/pkg/tests/testthat/test-alignMatrices.R
@@ -4,7 +4,7 @@ context("alignMatrices")
 .generateMatrices = function(d, K, N, noise)
 {
   matrices = list( matrix(runif(d*K, min=-1, max=1),ncol=K) ) #reference
-  for (i in 2:N)
+  for (i in 2:(N+1))
   {
     matrices[[i]] <- matrices[[1]][,sample(1:K)]
     if (noise)
@@ -15,55 +15,50 @@ context("alignMatrices")
 
 test_that("labelSwitchingAlign correctly aligns de-noised parameters",
 {
-  N = 30 #number of matrices
-  d_K_list = list(c(2,2), c(5,3))
+  N <- 30 #number of matrices
+  d_K_list <- list(c(2,2), c(5,3))
   for (i in 1:2)
   {
-    d = d_K_list[[i]][1]
-    K = d_K_list[[i]][2]
+    d <- d_K_list[[i]][1]
+    K <- d_K_list[[i]][2]
 
     # 1] Generate matrix series
-    matrices_permut = .generateMatrices(d,K,N,noise=FALSE)
+    Ms <- .generateMatrices(d, K, N, noise=FALSE)
 
     # 2] Call align function with mode=approx1
-    matrices_aligned =
-      alignMatrices(matrices_permut[2:N], ref=matrices_permut[[1]], ls_mode="approx1")
+    aligned <- alignMatrices(Ms[2:(N+1)], ref=Ms[[1]], ls_mode="approx1")
 
     # 3] Check alignment
-    for (j in 2:N)
-      expect_equal(matrices_aligned[[j-1]], matrices_permut[[1]])
+    for (j in 1:N)
+      expect_equal(aligned[[j]], Ms[[1]])
 
     # 2bis] Call align function with mode=approx2
-    matrices_aligned =
-      alignMatrices(matrices_permut[2:N], ref=matrices_permut[[1]], ls_mode="approx2")
+    aligned <- alignMatrices(Ms[2:(N+1)], ref=Ms[[1]], ls_mode="approx2")
 
     # 3bis] Check alignment
-    for (j in 2:N)
-      expect_equal(matrices_aligned[[j-1]], matrices_permut[[1]])
+    for (j in 1:N)
+      expect_equal(aligned[[j]], Ms[[1]])
   }
 })
 
 test_that("labelSwitchingAlign correctly aligns noisy parameters",
 {
-  N = 30 #number of matrices
-  d_K_list = list(c(2,2), c(5,3))
+  N <- 30 #number of matrices
+  d_K_list <- list(c(2,2), c(5,3))
   for (i in 1:2)
   {
-    d = d_K_list[[i]][1]
-    K = d_K_list[[i]][2]
-    max_error = d * 0.2 #TODO: what value to choose ?
+    d <- d_K_list[[i]][1]
+    K <- d_K_list[[i]][2]
+    max_error <- d * 0.2 #TODO: what value to choose ?
 
     # 1] Generate matrix series
-    matrices_permut = .generateMatrices(d,K,N,noise=TRUE)
+    Ms <- .generateMatrices(d, K, N, noise=TRUE)
 
     # 2] Call align function
-    matrices_aligned = alignMatrices(matrices_permut, ref="mean", ls_mode="exact")
+    aligned <- alignMatrices(Ms[2:(N+1)], ref=Ms[[1]], ls_mode="exact")
 
     # 3] Check alignment
     for (j in 2:N)
-    {
-      expect_that( norm(matrices_aligned[[j]] - matrices_permut[[1]]),
-        is_less_than(max_error) )
-    }
+      expect_that( norm(aligned[[j]] - Ms[[1]]), is_less_than(max_error) )
   }
 })