+ if (verbose)
+ cat(paste("--- Compute synchrones\n", sep=""))
+
+ computeSynchronesChunk = function(indices)
+ {
+ ref_series = getRefSeries(indices)
+ nb_series = nrow(ref_series)
+
+ if (parll)
+ {
+ require("bigmemory", quietly=TRUE)
+ require("synchronicity", quietly=TRUE)
+ require("epclust", quietly=TRUE)
+ synchrones <- bigmemory::attach.big.matrix(synchrones_desc)
+ medoids <- bigmemory::attach.big.matrix(medoids_desc)
+ 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)
+
+# #R-equivalent, requiring a matrix (thus potentially breaking "fit-in-memory" hope)
+# mat_meds = medoids[,]
+# mi = rep(NA,nb_series)
+# for (i in 1:nb_series)
+# mi[i] <- which.min( rowSums( sweep(mat_meds, 2, ref_series[i,], '-')^2 ) )
+# rm(mat_meds); gc()
+
+ for (i in seq_len(nb_series))
+ {
+ if (parll)
+ synchronicity::lock(m)
+ synchrones[mi[i],] = synchrones[mi[i],] + ref_series[i,]
+ counts[mi[i],1] = counts[mi[i],1] + 1
+ if (parll)
+ synchronicity::unlock(m)
+ }
+ }
+
+ K = nrow(medoids) ; L = ncol(medoids)
+ # Use bigmemory (shared==TRUE by default) + synchronicity to fill synchrones in //
+ # TODO: if size > RAM (not our case), use file-backed big.matrix
+ synchrones = bigmemory::big.matrix(nrow=K, ncol=L, type="double", init=0.)
+ counts = bigmemory::big.matrix(nrow=K, ncol=1, type="double", init=0)
+ # synchronicity is only for Linux & MacOS; on Windows: run sequentially
+ parll = (requireNamespace("synchronicity",quietly=TRUE)
+ && parll && Sys.info()['sysname'] != "Windows")
+ if (parll)
+ {
+ m <- synchronicity::boost.mutex()
+ m_desc <- synchronicity::describe(m)
+ synchrones_desc = bigmemory::describe(synchrones)
+ medoids_desc = bigmemory::describe(medoids)
+
+ cl = parallel::makeCluster(ncores_clust)
+ parallel::clusterExport(cl,
+ varlist=c("synchrones_desc","counts","verbose","m_desc","medoids_desc","getRefSeries"),
+ envir=environment())
+ }
+
+ indices_workers = .spreadIndices(seq_len(nb_ref_curves), nb_series_per_chunk)
+ ignored <-
+ if (parll)
+ parallel::parLapply(cl, indices_workers, computeSynchronesChunk)
+ else
+ lapply(indices_workers, computeSynchronesChunk)