# observations node with CWT
Xcwt4 <- toCWT(conso, noctave = noctave4, dt = 1, scalevector = scalevector4, lt = delta,
smooth = FALSE, nvoice = nvoice)
# observations node with CWT
Xcwt4 <- toCWT(conso, noctave = noctave4, dt = 1, scalevector = scalevector4, lt = delta,
smooth = FALSE, nvoice = nvoice)
#matrix:
############Xcwt2 <- matrix(0.0, nrow= n, ncol= 2 + delta * lscvect)
Xcwt2 <- matrix(NA_complex_, nrow= n, ncol= 2 + length((c(Xcwt4[,,1]))))
#matrix:
############Xcwt2 <- matrix(0.0, nrow= n, ncol= 2 + delta * lscvect)
Xcwt2 <- matrix(NA_complex_, nrow= n, ncol= 2 + length((c(Xcwt4[,,1]))))
Xcwt2[i,] <- c(delta, lscvect, Xcwt4[,,i] / max(Mod(Xcwt4[,,i])) )
#rm(conso, Xcwt4); gc()
Xcwt2[i,] <- c(delta, lscvect, Xcwt4[,,i] / max(Mod(Xcwt4[,,i])) )
#rm(conso, Xcwt4); gc()
## _.b WER^2 distances ########
Xwer_dist <- matrix(0.0, n, n)
for(i in 1:(n - 1))
{
## _.b WER^2 distances ########
Xwer_dist <- matrix(0.0, n, n)
for(i in 1:(n - 1))
{
mat1 <- vect2mat(Xcwt2[i,], delta, lscvect)
for(j in (i + 1):n)
mat1 <- vect2mat(Xcwt2[i,], delta, lscvect)
for(j in (i + 1):n)