fix typo, add some TODO

diff --git a/.gitignore b/.gitignore
index c946480..c8ea425 100644 (file)
--- 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 (file)
--- 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 (file)
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 (file)
--- 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()