1 context("computeSynchrones")
3 test_that("computeSynchrones behave as expected",
5 # Generate 300 sinusoïdal series of 3 kinds: all series of indices == 0 mod 3 are the same
6 # (plus noise), all series of indices == 1 mod 3 are the same (plus noise) ...
13 s3 = c( s1[1:(L%/%2)] , s2[(L%/%2+1):L] )
18 series = matrix(nrow=L, ncol=n)
20 series[,i] = s[[I(i,K)]] + rnorm(L,sd=0.01)
22 getRefSeries = function(indices) {
23 indices = indices[indices <= n]
24 if (length(indices)>0) as.matrix(series[,indices]) else NULL
27 synchrones = computeSynchrones(bigmemory::as.big.matrix(cbind(s1,s2,s3)), getRefSeries,
28 n, 100, verbose=TRUE, parll=FALSE)
30 expect_equal(dim(synchrones), c(L,K))
33 # Synchrones are (for each medoid) sums of closest curves.
34 # Here, we expect exactly 100 curves of each kind to be assigned respectively to
35 # synchrone 1, 2 and 3 => division by 100 should be very close to the ref curve
36 expect_equal(synchrones[,i]/100, s[[i]], tolerance=0.01)