X-Git-Url: https://git.auder.net/?p=epclust.git;a=blobdiff_plain;f=epclust%2FR%2Fclustering.R;fp=epclust%2FR%2Fstage2.R;h=e27ea353e479fb8185afb124f02fbcab56c9d4e0;hp=3ccbbad10903b256c005b0476b418bf3bbfdd9a3;hb=5c6529795907ba1b34d4552cbfd0e0cbb77cac0f;hpb=db6fc17ddd53fb0c64cf957296dc615ba830db56

diff --git a/epclust/R/stage2.R b/epclust/R/clustering.R
similarity index 53%
rename from epclust/R/stage2.R
rename to epclust/R/clustering.R
index 3ccbbad..e27ea35 100644
--- a/epclust/R/stage2.R
+++ b/epclust/R/clustering.R
@@ -1,8 +1,66 @@
-library("Rwave")
+oneIteration = function(..........)
+{
+		cl_clust = parallel::makeCluster(ncores_clust)
+		parallel::clusterExport(cl_clust, .............., envir=........)
+		indices_clust = indices_task[[i]]
+		repeat
+		{
+			nb_workers = max( 1, round( length(indices_clust) / nb_series_per_chunk ) )
+			indices_workers = list()
+			#indices[[i]] == (start_index,number_of_elements)
+			for (i in 1:nb_workers)
+			{
+				upper_bound = ifelse( i<nb_workers,
+					min(nb_series_per_chunk*i,length(indices_clust)), length(indices_clust) )
+				indices_workers[[i]] = indices_clust[(nb_series_per_chunk*(i-1)+1):upper_bound]
+			}
+			indices_clust = parallel::parSapply(cl, indices_workers, processChunk, K1, K2*(WER=="mix"))
+			if ( (WER=="end" && length(indices_clust) == K1) ||
+				(WER=="mix" && length(indices_clust) == K2) )
+			{
+				break
+			}
+		}
+		parallel::stopCluster(cl_clust)
+		res_clust
+}
+
+processChunk = function(indices, K1, K2)
+{
+	#1) retrieve data (coeffs)
+	coeffs = getCoeffs(indices)
+	#2) cluster
+	cl = computeClusters(as.matrix(coeffs[,2:ncol(coeffs)]), K1)
+	#3) WER (optional)
+	if (K2 > 0)
+	{
+		curves = computeSynchrones(cl)
+		dists = computeWerDists(curves)
+		cl = computeClusters(dists, K2)
+	}
+	cl
+}
+
+computeClusters = function(data, K)
+{
+	library(cluster)
+	pam_output = cluster::pam(data, K)
+	return ( list( clusts=pam_output$clustering, medoids=pam_output$medoids,
+		ranks=pam_output$id.med ) )
+}
+
+#TODO: appendCoeffs() en C --> serialize et append to file
+
+computeSynchrones = function(...)
+{
+
+}
 
 #Entrée : courbes synchrones, soit après étape 1 itérée, soit après chaqure étape 1
-step2 = function(conso)
+computeWerDist = function(conso)
 {
+	if (!require("Rwave", quietly=TRUE))
+		stop("Unable to load Rwave library")
 	n <- nrow(conso)
 	delta <- ncol(conso)
 	#TODO: automatic tune of all these parameters ? (for other users)