From: Benjamin Auder <benjamin.auder@somewhere>
Date: Thu, 9 Mar 2017 16:22:09 +0000 (+0100)
Subject: draft final form of current package
X-Git-Url: https://git.auder.net/doc/html/css/scripts/%7B%7B%20asset%28%27mixstore/%7B%7B?a=commitdiff_plain;h=a174b8ea1f322992068ab42810df017a2b9620ee;p=epclust.git

draft final form of current package
---

diff --git a/TODO b/TODO
index 52b139d..53b4c97 100644
--- a/TODO
+++ b/TODO
@@ -65,3 +65,5 @@ réduire taille 17519 trop long ?
 synchrone : sum
 cwt : trim R part
 // : clever by rows retenir cwt...
+
+Stockage matrices : en colonnes systématiquement ?
diff --git a/epclust/R/clustering.R b/epclust/R/clustering.R
index 4519f44..a4c273a 100644
--- a/epclust/R/clustering.R
+++ b/epclust/R/clustering.R
@@ -67,8 +67,8 @@ clusteringTask1 = function(
 
 #' @rdname clustering
 #' @export
-clusteringTask2 = function(medoids, K2,
-	getRefSeries, nb_ref_curves, nb_series_per_chunk, ncores_clust=1,verbose=FALSE,parll=TRUE)
+clusteringTask2 = function(medoids, K2, getRefSeries, nb_ref_curves,
+	nb_series_per_chunk, nbytes,endian,ncores_clust=1,verbose=FALSE,parll=TRUE)
 {
 	if (verbose)
 		cat(paste("*** Clustering task 2 on ",nrow(medoids)," lines\n", sep=""))
@@ -77,7 +77,7 @@ clusteringTask2 = function(medoids, K2,
 		return (medoids)
 	synchrones = computeSynchrones(medoids,
 		getRefSeries, nb_ref_curves, nb_series_per_chunk, ncores_clust, verbose, parll)
-	distances = computeWerDists(synchrones, ncores_clust, verbose, parll)
+	distances = computeWerDists(synchrones, nbytes, endian, ncores_clust, verbose, parll)
 	medoids[ computeClusters2(distances,K2,verbose), ]
 }
 
@@ -203,7 +203,7 @@ computeSynchrones = function(medoids, getRefSeries,
 #' @return A matrix of size K1 x K1
 #'
 #' @export
-computeWerDists = function(synchrones, ncores_clust=1,verbose=FALSE,parll=TRUE)
+computeWerDists = function(synchrones, nbytes,endian,ncores_clust=1,verbose=FALSE,parll=TRUE)
 {
 	if (verbose)
 		cat(paste("--- Compute WER dists\n", sep=""))
@@ -218,8 +218,8 @@ computeWerDists = function(synchrones, ncores_clust=1,verbose=FALSE,parll=TRUE)
 	#NOTE: default scalevector == 2^(0:(noctave * nvoice) / nvoice) * s0 (?)
 	scalevector  <- 2^(4:(noctave * nvoice) / nvoice + 1)
 	#condition: ( log2(s0*w0/(2*pi)) - 1 ) * nvoice + 1.5 >= 1
-	s0=2
-	w0=2*pi
+	s0 = 2
+	w0 = 2*pi
 	scaled=FALSE
 	s0log = as.integer( (log2( s0*w0/(2*pi) ) - 1) * nvoice + 1.5 )
 	totnoct = noctave + as.integer(s0log/nvoice) + 1
@@ -237,7 +237,7 @@ computeWerDists = function(synchrones, ncores_clust=1,verbose=FALSE,parll=TRUE)
 		V = V[-1]
 		pairs = c(pairs, lapply(V, function(v) c(i,v)))
 	}
-	
+
 	computeSaveCWT = function(index)
 	{
 		ts <- scale(ts(synchrones[index,]), center=TRUE, scale=scaled)
@@ -249,7 +249,7 @@ computeWerDists = function(synchrones, ncores_clust=1,verbose=FALSE,parll=TRUE)
 		res <- sqres / max(Mod(sqres))
 		#TODO: serializer les CWT, les récupérer via getDataInFile ;
 		#--> OK, faut juste stocker comme séries simples de taille delta*ncol (53*17519)
-		binarize(res, cwt_file, 100, ",", nbytes, endian)
+		binarize(c(as.double(Re(res)),as.double(Im(res))), cwt_file, ncol(res), ",", nbytes, endian)
 	}
 
 	if (parll)
@@ -271,6 +271,8 @@ computeWerDists = function(synchrones, ncores_clust=1,verbose=FALSE,parll=TRUE)
 	getCWT = function(index)
 	{
 		#from cwt_file ...
+		res <- getDataInFile(c(2*index-1,2*index), cwt_file, nbytes, endian)
+	###############TODO:	
 	}
 
 	# Distance between rows i and j
diff --git a/epclust/R/main.R b/epclust/R/main.R
index 9ba23ae..28217c3 100644
--- a/epclust/R/main.R
+++ b/epclust/R/main.R
@@ -172,8 +172,8 @@ claws = function(getSeries, K1, K2,
 		{
 			require("bigmemory", quietly=TRUE)
 			medoids1 = bigmemory::as.big.matrix( getSeries(indices_medoids) )
-			medoids2 = clusteringTask2(medoids1,
-				K2, getSeries, nb_curves, nb_series_per_chunk, ncores_clust, verbose, parll)
+			medoids2 = clusteringTask2(medoids1, K2, getSeries, nb_curves, nb_series_per_chunk,
+				nbytes, endian, ncores_clust, verbose, parll)
 			binarize(medoids2, synchrones_file, nb_series_per_chunk, sep, nbytes, endian)
 			return (vector("integer",0))
 		}
@@ -235,8 +235,8 @@ claws = function(getSeries, K1, K2,
 	indices_medoids = clusteringTask1(
 		indices, getContribs, K1, nb_series_per_chunk, ncores_tasks*ncores_clust, verbose, parll)
 	medoids1 = bigmemory::as.big.matrix( getSeries(indices_medoids) )
-	medoids2 = clusteringTask2(medoids1, K2,
-		getRefSeries, nb_curves, nb_series_per_chunk, ncores_tasks*ncores_clust, verbose, parll)
+	medoids2 = clusteringTask2(medoids1, K2, getRefSeries, nb_curves, nb_series_per_chunk,
+		nbytes, endian, ncores_tasks*ncores_clust, verbose, parll)
 
 	# Cleanup
 	unlink(bin_dir, recursive=TRUE)