X-Git-Url: https://git.auder.net/?p=epclust.git;a=blobdiff_plain;f=epclust%2Ftests%2Ftestthat%2Ftest.filter.R;h=9d1916dbc1d98a58149c4c46ef84c173a06e09bb;hp=d94a5ac8052f1e9261bead01498c9e4a51fd4ee0;hb=0486fbadb122cb4d78c5d9f248c29800a59eb24e;hpb=37c82bbafbffc19e8b47a521952bac58f189e9ea

diff --git a/epclust/tests/testthat/test.filter.R b/epclust/tests/testthat/test.filter.R
index d94a5ac..9d1916d 100644
--- a/epclust/tests/testthat/test.filter.R
+++ b/epclust/tests/testthat/test.filter.R
@@ -1,8 +1,18 @@
-TODO: test computeMedoids + filter
-#		#R-equivalent, requiring a matrix (thus potentially breaking "fit-in-memory" hope)
-#		mat_meds = medoids[,]
-#		mi = rep(NA,nb_series)
-#		for (i in 1:nb_series)
-#			mi[i] <- which.min( rowSums( sweep(mat_meds, 2, ref_series[i,], '-')^2 ) )
-#		rm(mat_meds); gc()
+context("epclustFilter")
 
+#TODO: find a better name
+test_that("[time-]serie filtering behave as expected",
+{
+	# Currently just a mean of 3 values
+	M = matrix(runif(1000,min=-7,max=7), ncol=10)
+	ref_fM = stats::filter(M, c(1/3,1/3,1/3), circular=FALSE)
+	fM = epclust:::.epclustFilter(M)
+
+	#Expect an agreement on all inner values
+	expect_equal(dim(fM), c(100,10))
+	expect_equal(fM[2:99,], ref_fM[,2:99])
+
+	#For border values, just apply a "by-hand" mean
+	expect_equal(fM[1,], colMeans(rbind(M[1,],M[2,],M[100,])))
+	expect_equal(fM[100,], colMeans(rbind(M[100,],M[99,],M[1,])))
+}