X-Git-Url: https://git.auder.net/?p=morpheus.git;a=blobdiff_plain;f=pkg%2Ftests%2Ftestthat%2Ftest-alignMatrices.R;h=63e4bd3ce6b0b33c2690aaf91b7589df3000298f;hp=59ad1d186eb5a5bf3676de945f265b8b089508a1;hb=ab35f6102896a49e86e853262c0650faa2931638;hpb=cbd88fe5729bf206a784238a2637aa60e697fcdc

diff --git a/pkg/tests/testthat/test-alignMatrices.R b/pkg/tests/testthat/test-alignMatrices.R
index 59ad1d1..63e4bd3 100644
--- a/pkg/tests/testthat/test-alignMatrices.R
+++ b/pkg/tests/testthat/test-alignMatrices.R
@@ -1,69 +1,62 @@
-context("alignMatrices")
-
 # Helper to generate a random series of matrices to align
 .generateMatrices = function(d, K, N, noise)
 {
-	matrices = list( matrix(runif(d*K, min=-1, max=1),ncol=K) ) #reference
-	for (i in 2:N)
-	{
-		matrices[[i]] <- matrices[[1]][,sample(1:K)]
-		if (noise)
-			matrices[[i]] = matrices[[i]] + matrix(rnorm(d*K, sd=0.05), ncol=K)
-	}
-	matrices
+  matrices = list( matrix(runif(d*K, min=-1, max=1),ncol=K) ) #reference
+  for (i in 2:(N+1))
+  {
+    matrices[[i]] <- matrices[[1]][,sample(1:K)]
+    if (noise)
+      matrices[[i]] = matrices[[i]] + matrix(rnorm(d*K, sd=0.05), ncol=K)
+  }
+  matrices
 }
 
 test_that("labelSwitchingAlign correctly aligns de-noised parameters",
 {
-	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]
-
-		# 1] Generate matrix series
-		matrices_permut = .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")
-
-		# 3] Check alignment
-		for (j in 2:N)
-			expect_equal(matrices_aligned[[j-1]], matrices_permut[[1]])
-
-		# 2bis] Call align function with mode=approx2
-		matrices_aligned =
-			alignMatrices(matrices_permut[2:N], ref=matrices_permut[[1]], ls_mode="approx2")
-
-		# 3bis] Check alignment
-		for (j in 2:N)
-			expect_equal(matrices_aligned[[j-1]], matrices_permut[[1]])
-	}
+  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]
+
+    # 1] Generate matrix series
+    Ms <- .generateMatrices(d, K, N, noise=FALSE)
+
+    # 2] Call align function with mode=approx1
+    aligned <- alignMatrices(Ms[2:(N+1)], ref=Ms[[1]], ls_mode="approx1")
+
+    # 3] Check alignment
+    for (j in 1:N)
+      expect_equal(aligned[[j]], Ms[[1]])
+
+    # 2bis] Call align function with mode=approx2
+    aligned <- alignMatrices(Ms[2:(N+1)], ref=Ms[[1]], ls_mode="approx2")
+
+    # 3bis] Check alignment
+    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))
-	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 ?
-
-		# 1] Generate matrix series
-		matrices_permut = .generateMatrices(d,K,N,noise=TRUE)
-
-		# 2] Call align function
-		matrices_aligned = alignMatrices(matrices_permut, ref="mean", 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) )
-		}
-	}
+  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 ?
+
+    # 1] Generate matrix series
+    Ms <- .generateMatrices(d, K, N, noise=TRUE)
+
+    # 2] Call align function
+    aligned <- alignMatrices(Ms[2:(N+1)], ref=Ms[[1]], ls_mode="exact")
+
+    # 3] Check alignment
+    for (j in 2:N)
+      expect_lt( norm(aligned[[j]] - Ms[[1]]), max_error )
+  }
 })