+++ /dev/null
-computeClusters
-computeSynchrones
-
-# Cluster one full task (nb_curves / ntasks series)
-clusteringTask = function(indices,getSeries,getSeriesForSynchrones,synchrones_file,
- getCoefs,K1,K2,nb_series_per_chunk,ncores,to_file,ftype)
-{
- cl = parallel::makeCluster(ncores)
- repeat
- {
- nb_workers = max( 1, round( length(indices) / nb_series_per_chunk ) )
- indices_workers = lapply(seq_len(nb_workers), function(i) {
- upper_bound = ifelse( i<nb_workers,
- min(nb_series_per_chunk*i,length(indices)), length(indices) )
- indices[(nb_series_per_chunk*(i-1)+1):upper_bound]
- })
- indices = unlist( parallel::parLapply(cl, indices_workers, function(inds)
- computeClusters1(inds, getCoefs, K1)) )
- if (length(indices_clust) == K1)
- break
- }
- parallel::stopCluster(cl)
- if (K2 == 0)
- return (indices)
- computeClusters2(indices, K2, getSeries, getSeriesForSynchrones, to_file,
- nb_series_per_chunk,ftype)
- vector("integer",0)
-}
-
-# Apply the clustering algorithm (PAM) on a coeffs or distances matrix
-computeClusters1 = function(indices, getCoefs, K1)
-{
- coefs = getCoefs(indices)
- indices[ cluster::pam(coefs, K1, diss=FALSE)$id.med ]
-}
-
-# Cluster a chunk of series inside one task (~max nb_series_per_chunk)
-computeClusters2 = function(indices, K2, getSeries, getSeriesForSynchrones, to_file,