X-Git-Url: https://git.auder.net/?a=blobdiff_plain;f=epclust%2FR%2Fclustering.R;h=9a55495bb6f650a3445c11b281ddef359dd0c4c2;hb=c45fd66342e40c8b5387fc6f0059c4d3a9718340;hp=74d009e45495220304a0087554e619d3c9efc4e4;hpb=492cd9e74a79cbcc0ecde55fa3071a44b7e463dc;p=epclust.git

diff --git a/epclust/R/clustering.R b/epclust/R/clustering.R
index 74d009e..9a55495 100644
--- a/epclust/R/clustering.R
+++ b/epclust/R/clustering.R
@@ -93,6 +93,8 @@ computeSynchrones = function(medoids, getRefSeries,
 {
 	computeSynchronesChunk = function(indices)
 	{
+		if (verbose)
+			cat(paste("--- Compute synchrones for ",length(indices)," lines\n", sep=""))
 		ref_series = getRefSeries(indices)
 		#get medoids indices for this chunk of series
 		for (i in seq_len(nrow(ref_series)))
@@ -118,20 +120,14 @@ computeSynchrones = function(medoids, getRefSeries,
 		m <- synchronicity::boost.mutex()
 
 	indices_workers = .spreadIndices(seq_len(nb_ref_curves), nb_series_per_chunk)
-	for (inds in indices_workers)
-	{
-		if (verbose)
+	ignored <-
+		if (parll)
 		{
-			cat(paste("--- Compute synchrones for indices range ",
-				min(inds)," -> ",max(inds),"\n", sep=""))
+			parallel::mclapply(indices_workers, computeSynchronesChunk,
+				mc.cores=ncores_clust, mc.allow.recursive=FALSE)
 		}
-		if (parll)
-			ignored <- parallel::mcparallel(computeSynchronesChunk(inds))
 		else
-			computeSynchronesChunk(inds)
-	}
-	if (parll)
-		parallel::mccollect()
+			lapply(indices_workers, computeSynchronesChunk)
 
 	mat_syncs = matrix(nrow=K, ncol=ncol(medoids))
 	vec_count = rep(NA, K)
@@ -184,14 +180,16 @@ computeWerDists = function(synchrones, ncores_clust=1,verbose=FALSE,parll=TRUE)
 		ts.cwt = totts.cwt[,s0log:(s0log+noctave*nvoice)]
 		#Normalization
 		sqs <- sqrt(2^(0:(noctave*nvoice)/nvoice)*s0)
-		sqres <- sweep(ts.cwt,MARGIN=2,sqs,'*')
+		sqres <- sweep(ts.cwt,2,sqs,'*')
 		sqres / max(Mod(sqres))
 	}
 
 	if (parll)
 	{
 		cl = parallel::makeCluster(ncores_clust)
-		parallel::clusterExport(cl, varlist=c("getContribs","K1","verbose"), envir=environment())
+		parallel::clusterExport(cl,
+			varlist=c("synchrones","totnoct","nvoice","w0","s0log","noctave","s0","verbose"),
+			envir=environment())
 	}
 
 	# (normalized) observations node with CWT
@@ -235,18 +233,16 @@ computeWerDists = function(synchrones, ncores_clust=1,verbose=FALSE,parll=TRUE)
 	if (parll)
 		m <- synchronicity::boost.mutex()
 
-	for (i in 1:(n-1))
-	{
+	ignored <-
 		if (parll)
-			ignored <- parallel::mcparallel(computeDistancesLineI(i))
+		{
+			parallel::mclapply(seq_len(n-1), computeDistancesLineI,
+				mc.cores=ncores_clust, mc.allow.recursive=FALSE)
+		}
 		else
-			computeDistancesLineI(i)
-	}
+			lapply(seq_len(n-1), computeDistancesLineI)
 	Xwer_dist[n,n] = 0.
 
-	if (parll)
-		parallel::mccollect()
-
 	mat_dists = matrix(nrow=n, ncol=n)
 	#TODO: avoid this loop?
 	for (i in 1:n)