From 2c14dbea13c897c6964f49f9cd17622f4c9733c0 Mon Sep 17 00:00:00 2001
From: Benjamin Auder <benjamin.auder@somewhere>
Date: Thu, 9 Mar 2017 11:58:25 +0100
Subject: [PATCH] fix typo, add some TODO

---
 .gitignore                                    |  4 ++
 TODO                                          | 12 ++++
 ...nal_Data_Using_Wavelets-Antoniadis2013.pdf |  1 +
 epclust/R/clustering.R                        | 58 +++++++------------
 4 files changed, 39 insertions(+), 36 deletions(-)
 create mode 100644 biblio/Clustering_Functional_Data_Using_Wavelets-Antoniadis2013.pdf

diff --git a/.gitignore b/.gitignore
index c946480..c8ea425 100644
--- a/.gitignore
+++ b/.gitignore
@@ -40,3 +40,7 @@
 #ignore RcppExports, generated by Rcpp::compileAttributes
 /epclust/R/RcppExports.R
 /epclust/src/RcppExports.cpp
+
+#misc
+Rprof.out
+*.zip
diff --git a/TODO b/TODO
index 199a59f..4f865b0 100644
--- a/TODO
+++ b/TODO
@@ -47,3 +47,15 @@ utiliser Rcpp ?
 #' @importFrom synchronicity boost.mutex lock unlock
 
 subtree: epclust, shared. This root folder should remain private
+
+#TODO: use dbs(),
+		#https://www.r-bloggers.com/debugging-parallel-code-with-dbs/
+		#http://gforge.se/2015/02/how-to-go-parallel-in-r-basics-tips/
+
+synchrones --> somme, pas moyenne
+
+PLOT:
+plot manifold 2D distances WER /
+fenetre tempo forme des courbes /
+medoids /
+gain en prevision: clust puis full --> enercast
diff --git a/biblio/Clustering_Functional_Data_Using_Wavelets-Antoniadis2013.pdf b/biblio/Clustering_Functional_Data_Using_Wavelets-Antoniadis2013.pdf
new file mode 100644
index 0000000..5801a64
--- /dev/null
+++ b/biblio/Clustering_Functional_Data_Using_Wavelets-Antoniadis2013.pdf
@@ -0,0 +1 @@
+#$# git-fat 7571c6c3b737bf2f57eab62fea99eb24a756eded               895937
diff --git a/epclust/R/clustering.R b/epclust/R/clustering.R
index 4d43b2b..7e06c43 100644
--- a/epclust/R/clustering.R
+++ b/epclust/R/clustering.R
@@ -134,29 +134,8 @@ computeSynchrones = function(medoids, getRefSeries,
 			m <- synchronicity::attach.mutex(m_desc)
 		}
 
-
-
-#TODO: use dbs(),
-		#https://www.r-bloggers.com/debugging-parallel-code-with-dbs/
-		#http://gforge.se/2015/02/how-to-go-parallel-in-r-basics-tips/
-
-#OK ::
-#write(length(indices), file="TOTO")
-#write( computeMedoidsIndices(medoids@address, getRefSeries(indices[1:600])), file="TOTO")
-#stop()
-
-#		write(indices, file="TOTO", ncolumns=10, append=TRUE)
-#write("medoids", file = "TOTO", ncolumns=1, append=TRUE)
-#write(medoids[1,1:3], file = "TOTO", ncolumns=1, append=TRUE)
-#write("synchrones", file = "TOTO", ncolumns=1, append=TRUE)
-#write(synchrones[1,1:3], file = "TOTO", ncolumns=1, append=TRUE)
-
-#NOT OK :: (should just be "ref_series") ...or yes ? race problems mutex then ? ?!
 		#get medoids indices for this chunk of series
-		mi = computeMedoidsIndices(medoids@address, getRefSeries(indices[1:600]))  #ref_series)
-write("MI ::::", file = "TOTO", ncolumns=1, append=TRUE)
-write(mi[1:3], file = "TOTO", ncolumns=1, append=TRUE)
-
+		mi = computeMedoidsIndices(medoids@address, ref_series)
 #		#R-equivalent, requiring a matrix (thus potentially breaking "fit-in-memory" hope)
 #		mat_meds = medoids[,]
 #		mi = rep(NA,nb_series)
@@ -169,6 +148,7 @@ write(mi[1:3], file = "TOTO", ncolumns=1, append=TRUE)
 			if (parll)
 				synchronicity::lock(m)
 			synchrones[mi[i],] = synchrones[mi[i],] + ref_series[i,]
+#TODO: remove counts
 			counts[mi[i],1] = counts[mi[i],1] + 1
 			if (parll)
 				synchronicity::unlock(m)
@@ -266,14 +246,17 @@ computeWerDists = function(synchrones, ncores_clust=1,verbose=FALSE,parll=TRUE)
 	# Distance between rows i and j
 	computeDistancesIJ = function(pair)
 	{
-		require("bigmemory", quietly=TRUE)
-		require("epclust", quietly=TRUE)
-		synchrones <- bigmemory::attach.big.matrix(synchrones_desc)
-		Xwer_dist <- bigmemory::attach.big.matrix(Xwer_dist_desc)
-	
-		computeCWT = function(i)
+		if (parll)
 		{
-			ts <- scale(ts(synchrones[i,]), center=TRUE, scale=scaled)
+			require("bigmemory", quietly=TRUE)
+			require("epclust", quietly=TRUE)
+			synchrones <- bigmemory::attach.big.matrix(synchrones_desc)
+			Xwer_dist <- bigmemory::attach.big.matrix(Xwer_dist_desc)
+		}
+
+		computeCWT = function(index)
+		{
+			ts <- scale(ts(synchrones[index,]), center=TRUE, scale=scaled)
 			totts.cwt = Rwave::cwt(ts, totnoct, nvoice, w0, plot=FALSE)
 			ts.cwt = totts.cwt[,s0log:(s0log+noctave*nvoice)]
 			#Normalization
@@ -281,18 +264,21 @@ computeWerDists = function(synchrones, ncores_clust=1,verbose=FALSE,parll=TRUE)
 			sqres <- sweep(ts.cwt,2,sqs,'*')
 			sqres / max(Mod(sqres))
 		}
-
+#browser()
 		i = pair[1] ; j = pair[2]
 		if (verbose && j==i+1)
 			cat(paste("   Distances (",i,",",j,"), (",i,",",j+1,") ...\n", sep=""))
-		cwt_i = computeCWT(i)
-		cwt_j = computeCWT(j)
+print(system.time( {		cwt_i <- computeCWT(i)
+		cwt_j <- computeCWT(j) } ))
+
+print(system.time( {
 		num <- epclustFilter(Mod(cwt_i * Conj(cwt_j)))
 		WX  <- epclustFilter(Mod(cwt_i * Conj(cwt_i)))
 		WY  <- epclustFilter(Mod(cwt_j * Conj(cwt_j)))
 		wer2 <- sum(colSums(num)^2) / sum(colSums(WX) * colSums(WY))
-		Xwer_dist[i,j] <- sqrt(delta * ncol(cwt_i) * (1 - wer2))
+		Xwer_dist[i,j] <- sqrt(delta * ncol(cwt_i) * max(1 - wer2, 0.)) #FIXME: wer2 should be < 1
 		Xwer_dist[j,i] <- Xwer_dist[i,j]
+} ) )
 		Xwer_dist[i,i] = 0.
 	}
 
@@ -300,12 +286,12 @@ computeWerDists = function(synchrones, ncores_clust=1,verbose=FALSE,parll=TRUE)
 	{
 		cl = parallel::makeCluster(ncores_clust)
 		synchrones_desc <- bigmemory::describe(synchrones)
-		Xwer_dist_desc_desc <- bigmemory::describe(Xwer_dist)
+		Xwer_dist_desc <- bigmemory::describe(Xwer_dist)
 
 		parallel::clusterExport(cl, varlist=c("synchrones_desc","Xwer_dist_desc","totnoct",
 			"nvoice","w0","s0log","noctave","s0","verbose"), envir=environment())
 	}
-
+browser()
 	ignored <-
 		if (parll)
 			parallel::parLapply(cl, pairs, computeDistancesIJ)
@@ -314,7 +300,7 @@ computeWerDists = function(synchrones, ncores_clust=1,verbose=FALSE,parll=TRUE)
 
 	if (parll)
 		parallel::stopCluster(cl)
-
+#browser()
 	Xwer_dist[n,n] = 0.
 	distances <- Xwer_dist[,]
 	rm(Xwer_dist) ; gc()
-- 
2.44.0