{
# Generate 300 sinusoïdal series of 3 kinds: all series of indices == 0 mod 3 are the same
# (plus noise), all series of indices == 1 mod 3 are the same (plus noise) ...
- n = 300
- x = seq(0,9.5,0.1)
- L = length(x) #96 1/4h
- K = 3
- s1 = cos(x)
- s2 = sin(x)
- s3 = c( s1[1:(L%/%2)] , s2[(L%/%2+1):L] )
+ n <- 300
+ x <- seq(0,9.5,0.1)
+ L <- length(x) #96 1/4h
+ K <- 3
+ s1 <- cos(x)
+ s2 <- sin(x)
+ s3 <- c( s1[1:(L%/%2)] , s2[(L%/%2+1):L] )
#sum((s1-s2)^2) == 96
#sum((s1-s3)^2) == 58
#sum((s2-s3)^2) == 38
- s = list(s1, s2, s3)
- series = matrix(nrow=L, ncol=n)
+ s <- list(s1, s2, s3)
+ series <- matrix(nrow=L, ncol=n)
for (i in seq_len(n))
- series[,i] = s[[I(i,K)]] + rnorm(L,sd=0.01)
+ series[,i] <- s[[I(i,K)]] + rnorm(L,sd=0.01)
- getRefSeries = function(indices) {
- indices = indices[indices <= n]
+ getSeries <- function(indices) {
+ indices <- indices[indices <= n]
if (length(indices)>0) as.matrix(series[,indices]) else NULL
}
- synchrones = computeSynchrones(bigmemory::as.big.matrix(cbind(s1,s2,s3)), getRefSeries,
- n, 100, verbose=TRUE, parll=FALSE)
+ synchrones <- computeSynchrones(cbind(s1,s2,s3),getSeries,n,100,verbose=TRUE,parll=FALSE)
expect_equal(dim(synchrones), c(L,K))
for (i in 1:K)