X-Git-Url: https://git.auder.net/?a=blobdiff_plain;f=epclust%2FR%2Fmain.R;h=27fbb7488394bcc39009c86b74251b3c458cce4b;hb=3eef8d3df59ded9a281cff51f79fe824198a7427;hp=ac4ea8ddc40567b72d84c240743fbc38d4e57971;hpb=0e2dce80a3fddaca50c96c6c27a8b32468095d6c;p=epclust.git

diff --git a/epclust/R/main.R b/epclust/R/main.R
index ac4ea8d..27fbb74 100644
--- a/epclust/R/main.R
+++ b/epclust/R/main.R
@@ -34,12 +34,13 @@
 #'     "LIMIT ", n, " ORDER BY date", sep=""))
 #'   return (df)
 #' }
+#' #####TODO: if DB, array rank --> ID at first retrieval, when computing coeffs; so:: NO use of IDs !
 #'   #TODO: 3 examples, data.frame / binary file / DB sqLite
 #'   + sampleCurves : wavBootstrap de package wmtsa
 #' cl = epclust(getData, K1=200, K2=15, ntasks=1000, nb_series_per_chunk=5000, WER="mix")
 #' @export
 epclust = function(series,K1,K2,ntasks=1,nb_series_per_chunk=50*K1,min_series_per_chunk=5*K1,
-	wf="haar",WER="end",ncores_tasks=1,ncores_clust=4,random=TRUE,...)
+	wf="haar",WER="end",ncores_tasks=1,ncores_clust=4,random=TRUE,ftype="float",...)
 {
 	# Check/transform arguments
 	bin_dir = "epclust.bin/"
@@ -50,7 +51,7 @@ epclust = function(series,K1,K2,ntasks=1,nb_series_per_chunk=50*K1,min_series_pe
 		unlink(series_file)
 	}
 	if (is.matrix(series))
-		serialize(series, series_file)
+		serialize(series, series_file, ftype, nb_series_per_chunk)
 	else if (!is.function(series))
 	{
 		tryCatch(
@@ -62,7 +63,7 @@ epclust = function(series,K1,K2,ntasks=1,nb_series_per_chunk=50*K1,min_series_pe
 					open(series)
 					series_con = series
 				}
-				serialize(series_con, series_file)
+				serialize(series_con, series_file, ftype, nb_series_per_chunk)
 				close(series_con)
 			},
 			error=function(e) "series should be a data.frame, a function or a valid connection"
@@ -93,12 +94,11 @@ epclust = function(series,K1,K2,ntasks=1,nb_series_per_chunk=50*K1,min_series_pe
 		if (is.null(series))
 			break
 		coeffs_chunk = curvesToCoeffs(series, wf)
-		serialize(coeffs_chunk, coefs_file)
+		serialize(coeffs_chunk, coefs_file, ftype, nb_series_per_chunk)
 		index = index + nb_series_per_chunk
 		nb_curves = nb_curves + nrow(coeffs_chunk)
 	}
 	getCoefs = function(indices) getDataInFile(indices, coefs_file)
-######TODO: if DB, array rank --> ID at first retrieval, when computing coeffs; so:: NO use of IDs !
 
 	if (nb_curves < min_series_per_chunk)
 		stop("Not enough data: less rows than min_series_per_chunk!")
@@ -112,17 +112,36 @@ epclust = function(series,K1,K2,ntasks=1,nb_series_per_chunk=50*K1,min_series_pe
 		upper_bound = ifelse( i<ntasks, min(nb_series_per_task*i,nb_curves), nb_curves )
 		indices[((i-1)*nb_series_per_task+1):upper_bound]
 	})
-	cl_tasks = parallel::makeCluster(ncores_tasks)
-	parallel::clusterExport(cl_tasks,
-		varlist=c("getSeries","getCoefs","K1","K2","WER","nb_series_per_chunk","ncores_clust"),
-		envir=environment())
+	cl = parallel::makeCluster(ncores_tasks)
 	#1000*K1 (or K2) indices (or NOTHING--> series on file)
-	indices = parallel::parLapply(cl_tasks, indices_tasks, clusteringTask)
-	parallel::stopCluster(cl_tasks)
+	indices = unlist( parallel::parLapply(cl, indices_tasks, function(inds) {
+		clusteringTask(inds, getSeries, getSeries, getCoefs, K1, K2*(WER=="mix"),
+			nb_series_per_chunk,ncores_clust,to_file=TRUE, ftype)
+	}) )
+	parallel::stopCluster(cl)
 
-	#Now series must be retrieved from synchrones_file, and have no ID
-	getSeries = function(indices, ids) getDataInFile(indices, synchrones_file)
+	getSeriesForSynchrones = getSeries
+	synchrones_file = paste(bin_dir,"synchrones",sep="")
+	if (WER=="mix")
+	{
+		indices = seq_len(ntasks*K2)
+		#Now series must be retrieved from synchrones_file
+		getSeries = function(inds) getDataInFile(inds, synchrones_file)
+		#Coefs must be re-computed
+		unlink(coefs_file)
+		index = 1
+		repeat
+		{
+			series = getSeries((index-1)+seq_len(nb_series_per_chunk))
+			if (is.null(series))
+				break
+			coeffs_chunk = curvesToCoeffs(series, wf)
+			serialize(coeffs_chunk, coefs_file, ftype, nb_series_per_chunk)
+			index = index + nb_series_per_chunk
+		}
+	}
 
 	# Run step2 on resulting indices or series (from file)
-	computeClusters2(indices=if (WER=="end") indices else NULL, K2, to_file=FALSE)
+	clusteringTask(indices, getSeries, getSeriesForSynchrones, getCoefs, K1, K2,
+		nb_series_per_chunk, ncores_tasks*ncores_clust, to_file=FALSE, ftype)
 }