X-Git-Url: https://git.auder.net/?p=epclust.git;a=blobdiff_plain;f=epclust%2FR%2Fclustering.R;h=70d263e951f68b1cdc742caf15cf46f4aaf0fe83;hp=14915abf861bace1b6d4bd4f9f68283c004bfff9;hb=2b9f5356793c245a5e10229a74ac0dabd8f62508;hpb=eef6f6c97277ea3ce760981e5244cbde7fc904a0

diff --git a/epclust/R/clustering.R b/epclust/R/clustering.R
index 14915ab..70d263e 100644
--- a/epclust/R/clustering.R
+++ b/epclust/R/clustering.R
@@ -11,8 +11,8 @@
 #'   and then WER distances computations, before applying the clustering algorithm.
 #'   \code{computeClusters1()} and \code{computeClusters2()} correspond to the atomic
 #'   clustering procedures respectively for stage 1 and 2. The former applies the
-#'   clustering algorithm (PAM) on a contributions matrix, while the latter clusters
-#'   a chunk of series inside one task (~max nb_series_per_chunk)
+#'   first clustering algorithm on a contributions matrix, while the latter clusters
+#'   a set of series inside one task (~nb_items_clust)
 #'
 #' @param indices Range of series indices to cluster in parallel (initial data)
 #' @param getContribs Function to retrieve contributions from initial series indices:
@@ -31,11 +31,23 @@ NULL
 #' @rdname clustering
 #' @export
 clusteringTask1 = function(
-	indices, getContribs, K1, nb_items_per_chunk, ncores_clust=1, verbose=FALSE, parll=TRUE)
+	indices, getContribs, K1, nb_per_chunk, nb_items_clust, ncores_clust=1,
+	verbose=FALSE, parll=TRUE)
 {
 	if (verbose)
 		cat(paste("*** Clustering task 1 on ",length(indices)," lines\n", sep=""))
 
+
+
+
+
+
+##TODO: reviser le spreadIndices, tenant compte de nb_items_clust
+
+	##TODO: reviser / harmoniser avec getContribs qui en récupère pt'et + pt'et - !!
+
+
+
 	if (parll)
 	{
 		cl = parallel::makeCluster(ncores_clust)