X-Git-Url: https://git.auder.net/?p=epclust.git;a=blobdiff_plain;f=epclust%2Ftests%2Ftestthat%2Ftest.computeMedoidsIndices.R;h=8347fb6fbf501a01d4e631fdc58f62bbec195658;hp=efd6af909d4cfcfa3017723afa427b2ee3c57896;hb=0fe757f750f51e580d2c5a7b7f7df87cc405d12d;hpb=0486fbadb122cb4d78c5d9f248c29800a59eb24e

diff --git a/epclust/tests/testthat/test.computeMedoidsIndices.R b/epclust/tests/testthat/test.computeMedoidsIndices.R
index efd6af9..8347fb6 100644
--- a/epclust/tests/testthat/test.computeMedoidsIndices.R
+++ b/epclust/tests/testthat/test.computeMedoidsIndices.R
@@ -8,17 +8,18 @@ test_that("computeMedoidsIndices behave as expected",
 	medoids = cbind( rep(0,L), rep(-5,L), rep(5,L) )
 	# short series...
 	series = t( rbind( MASS::mvrnorm(n/3, medoids[,1], diag(L)),
-		MASS::mvrnorm(n/3, medoids[,2], diag(L),
-		MASS::mvrnorm(n/3, medoids[,3], diag(L))) ) )
+		MASS::mvrnorm(n/3, medoids[,2], diag(L)),
+		MASS::mvrnorm(n/3, medoids[,3], diag(L)) ) )
 
 	# With high probability, medoids indices should resemble 1,1,1,...,2,2,2,...,3,3,3,...
-	mi = epclust:::.computeMedoidsIndices(medoids, series)
+	require("bigmemory", quietly=TRUE)
+	mi = epclust:::computeMedoidsIndices(bigmemory::as.big.matrix(medoids)@address, series)
 	mi_ref = rep(1:3, each=n/3)
-	expect_that( mean(mi != mi_ref) < 0.01 )
+	expect_lt( mean(mi != mi_ref), 0.01 )
 
 	# Now with a random matrix, compare with (trusted) R version
 	series = matrix(runif(n*L, min=-7, max=7), nrow=L)
-	mi = epclust:::.computeMedoidsIndices(medoids, series)
+	mi = epclust:::computeMedoidsIndices(bigmemory::as.big.matrix(medoids)@address, series)
 	mi_ref = R_computeMedoidsIndices(medoids, series)
 	expect_equal(mi, mi_ref)
 })