X-Git-Url: https://git.auder.net/?p=epclust.git;a=blobdiff_plain;f=pkg%2FR%2FcomputeSynchrones.R;fp=pkg%2FR%2FcomputeSynchrones.R;h=3a29546c8fed64636f9e2de286f38897b3c04dcc;hp=0000000000000000000000000000000000000000;hb=e906736ea27105237e84c904dce6170353726292;hpb=57f337af19cd6251815bb1ff2d62f4c58e8b6078

diff --git a/pkg/R/computeSynchrones.R b/pkg/R/computeSynchrones.R
new file mode 100644
index 0000000..3a29546
--- /dev/null
+++ b/pkg/R/computeSynchrones.R
@@ -0,0 +1,67 @@
+#' computeSynchrones
+#'
+#' Compute the synchrones curves (sums of clusters elements) from a matrix of medoids,
+#' using euclidian distance.
+#'
+#' @param medoids matrix of K medoids curves in columns
+#' @param nb_curves How many series? (this is known, at this stage)
+#' @inheritParams claws
+#' @inheritParams computeWerDists
+#'
+#' @return A matrix of K synchrones in columns (same length as the series)
+#'
+#' @export
+computeSynchrones <- function(medoids, getSeries, nb_curves,
+	nb_series_per_chunk, ncores=3, verbose=FALSE)
+{
+	# Synchrones computation is embarassingly parallel: compute it by chunks of series
+	computeSynchronesChunk <- function(indices)
+	{
+		# Obtain a chunk of reference series
+		series_chunk <- getSeries(indices)
+		nb_series_chunk <- ncol(series_chunk)
+
+		# Get medoids indices for this chunk of series
+		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
+		for (i in seq_len(K))
+		{
+			# lock / unlock required because several writes at the same time
+			if (parll)
+				synchronicity::lock(m)
+			synchrones[,i] <- synchrones[,i] + rowSums(as.matrix(series_chunk[,mi==i]))
+			if (parll)
+				synchronicity::unlock(m)
+		}
+		NULL
+	}
+
+	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.)
+	# NOTE: synchronicity is only for Linux & MacOS; on Windows: run sequentially
+	parll <- (ncores > 1 && requireNamespace("synchronicity",quietly=TRUE)
+		&& Sys.info()['sysname'] != "Windows")
+
+	if (parll)
+		m <- synchronicity::boost.mutex() #for lock/unlock, see computeSynchronesChunk
+
+	if (verbose)
+		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)
+	ignored <-
+		if (parll)
+		{
+			parallel::mclapply(indices_workers,
+				function(inds) computeSynchronesChunk(inds), mc.cores=ncores)
+		}
+		else
+			lapply(indices_workers, computeSynchronesChunk)
+
+	return (synchrones[,])
+}