X-Git-Url: https://git.auder.net/?p=epclust.git;a=blobdiff_plain;f=epclust%2FR%2FcomputeSynchrones.R;h=16bf0b44939fcd760b52ed5fff693e52a4dcfcee;hp=09ff3a09aae87d539902dcb9790f9312cc1c47d3;hb=282342bafdc9ff65c5df98c6e2304d63b33b9fb2;hpb=3c5a4b0880db63367a474a568e1322b3999932fe

diff --git a/epclust/R/computeSynchrones.R b/epclust/R/computeSynchrones.R
index 09ff3a0..16bf0b4 100644
--- a/epclust/R/computeSynchrones.R
+++ b/epclust/R/computeSynchrones.R
@@ -11,11 +11,11 @@
 #' @return A matrix of K synchrones in columns (same length as the series)
 #'
 #' @export
-computeSynchrones = function(medoids, getSeries, nb_curves,
+computeSynchrones <- function(medoids, getSeries, nb_curves,
 	nb_series_per_chunk, ncores_clust=1,verbose=FALSE,parll=TRUE)
 {
 	# Synchrones computation is embarassingly parallel: compute it by chunks of series
-	computeSynchronesChunk = function(indices)
+	computeSynchronesChunk <- function(indices)
 	{
 		if (parll)
 		{
@@ -29,12 +29,11 @@ computeSynchrones = function(medoids, getSeries, nb_curves,
 		}
 
 		# Obtain a chunk of reference series
-		series_chunk = getSeries(indices)
-		nb_series_chunk = ncol(series_chunk)
+		series_chunk <- getSeries(indices)
+		nb_series_chunk <- ncol(series_chunk)
 
 		# Get medoids indices for this chunk of series
-		for (i in seq_len(nb_series_chunk))
-			mi[i] <- which.min( colSums( sweep(medoids, 1, series_chunk[,i], '-')^2 ) )
+		mi <- assignMedoids(series_chunk, medoids[,])
 
 		# Update synchrones using mi above, grouping it by values of mi (in 1...K)
 		# to avoid too many lock/unlock
@@ -43,19 +42,19 @@ computeSynchrones = function(medoids, getSeries, nb_curves,
 			# lock / unlock required because several writes at the same time
 			if (parll)
 				synchronicity::lock(m)
-			synchrones[,i] = synchrones[,i] + rowSums(series_chunk[,mi==i])
+			synchrones[,i] <- synchrones[,i] + rowSums(as.matrix(series_chunk[,mi==i]))
 			if (parll)
 				synchronicity::unlock(m)
 		}
 		NULL
 	}
 
-	K = ncol(medoids)
-	L = nrow(medoids)
+	K <- ncol(medoids)
+	L <- nrow(medoids)
 	# Use bigmemory (shared==TRUE by default) + synchronicity to fill synchrones in //
-	synchrones = bigmemory::big.matrix(nrow=L, ncol=K, type="double", init=0.)
+	synchrones <- bigmemory::big.matrix(nrow=L, ncol=K, type="double", init=0.)
 	# NOTE: synchronicity is only for Linux & MacOS; on Windows: run sequentially
-	parll = (parll && requireNamespace("synchronicity",quietly=TRUE)
+	parll <- (parll && requireNamespace("synchronicity",quietly=TRUE)
 		&& Sys.info()['sysname'] != "Windows")
 	if (parll)
 	{
@@ -63,10 +62,11 @@ computeSynchrones = function(medoids, getSeries, nb_curves,
 		# mutex and big.matrix objects cannot be passed directly:
 		# they will be accessed from their description
 		m_desc <- synchronicity::describe(m)
-		synchrones_desc = bigmemory::describe(synchrones)
+		synchrones_desc <- bigmemory::describe(synchrones)
 		medoids <- bigmemory::as.big.matrix(medoids)
 		medoids_desc <- bigmemory::describe(medoids)
-		cl = parallel::makeCluster(ncores_clust)
+		# outfile=="" to see stderr/stdout on terminal
+		cl <- parallel::makeCluster(ncores_clust, outfile="")
 		parallel::clusterExport(cl, envir=environment(),
 			varlist=c("synchrones_desc","m_desc","medoids_desc","getSeries"))
 	}
@@ -75,7 +75,7 @@ computeSynchrones = function(medoids, getSeries, nb_curves,
 		cat(paste("--- Compute ",K," synchrones with ",nb_curves," series\n", sep=""))
 
 	# Balance tasks by splitting 1:nb_curves into groups of size <= nb_series_per_chunk
-	indices_workers = .splitIndices(seq_len(nb_curves), nb_series_per_chunk)
+	indices_workers <- .splitIndices(seq_len(nb_curves), nb_series_per_chunk)
 	ignored <-
 		if (parll)
 			parallel::parLapply(cl, indices_workers, computeSynchronesChunk)