Remove parll arg (redundant with ncores_XX)

[epclust.git] / epclust / R / computeSynchrones.R

diff --git a/epclust/R/computeSynchrones.R b/epclust/R/computeSynchrones.R
index f8d7a06..3a29546 100644 (file)
--- a/epclust/R/computeSynchrones.R
+++ b/epclust/R/computeSynchrones.R
@@ -4,30 +4,19 @@
 #' using euclidian distance.
 #'
 #' @param medoids matrix of K medoids curves in columns
-#' @param getSeries Function to retrieve series (argument: 'indices', integer vector),
-#'   as columns of a matrix
 #' @param nb_curves How many series? (this is known, at this stage)
 #' @inheritParams claws
+#' @inheritParams computeWerDists
 #'
 #' @return A matrix of K synchrones in columns (same length as the series)
 #'
 #' @export
 computeSynchrones <- function(medoids, getSeries, nb_curves,
-       nb_series_per_chunk, ncores_clust=3, verbose=FALSE, parll=TRUE)
+       nb_series_per_chunk, ncores=3, verbose=FALSE)
 {
        # Synchrones computation is embarassingly parallel: compute it by chunks of series
        computeSynchronesChunk <- function(indices)
        {
-               if (parll)
-               {
-                       require("epclust", quietly=TRUE)
-                       requireNamespace("synchronicity", quietly=TRUE)
-                       # The big.matrix objects need to be attached to be usable on the workers
-                       synchrones <- bigmemory::attach.big.matrix(synchrones_desc)
-                       medoids <- bigmemory::attach.big.matrix(medoids_desc)
-                       m <- synchronicity::attach.mutex(m_desc)
-               }
-
                # Obtain a chunk of reference series
                series_chunk <- getSeries(indices)
                nb_series_chunk <- ncol(series_chunk)
@@ -54,26 +43,11 @@ computeSynchrones <- function(medoids, getSeries, nb_curves,
        # Use bigmemory (shared==TRUE by default) + synchronicity to fill synchrones in //
        synchrones <- bigmemory::big.matrix(nrow=L, ncol=K, type="double", init=0.)
        # NOTE: synchronicity is only for Linux & MacOS; on Windows: run sequentially
-       parll <- (parll && requireNamespace("synchronicity",quietly=TRUE)
+       parll <- (ncores > 1 && requireNamespace("synchronicity",quietly=TRUE)
                && Sys.info()['sysname'] != "Windows")
+
        if (parll)
-       {
                m <- synchronicity::boost.mutex() #for lock/unlock, see computeSynchronesChunk
-               # mutex and big.matrix objects cannot be passed directly:
-               # they will be accessed from their description
-               m_desc <- synchronicity::describe(m)
-               synchrones_desc <- bigmemory::describe(synchrones)
-               medoids <- bigmemory::as.big.matrix(medoids)
-               medoids_desc <- bigmemory::describe(medoids)
-               # outfile=="" to see stderr/stdout on terminal
-               cl <-
-                       if (verbose)
-                               parallel::makeCluster(ncores_clust, outfile="")
-                       else
-                               parallel::makeCluster(ncores_clust)
-               parallel::clusterExport(cl, envir=environment(),
-                       varlist=c("synchrones_desc","m_desc","medoids_desc","getSeries"))
-       }
 
        if (verbose)
                cat(paste("--- Compute ",K," synchrones with ",nb_curves," series\n", sep=""))
@@ -82,12 +56,12 @@ computeSynchrones <- function(medoids, getSeries, nb_curves,
        indices_workers <- .splitIndices(seq_len(nb_curves), nb_series_per_chunk)
        ignored <-
                if (parll)
-                       parallel::parLapply(cl, indices_workers, computeSynchronesChunk)
+               {
+                       parallel::mclapply(indices_workers,
+                               function(inds) computeSynchronesChunk(inds), mc.cores=ncores)
+               }
                else
                        lapply(indices_workers, computeSynchronesChunk)
 
-       if (parll)
-               parallel::stopCluster(cl)
-
        return (synchrones[,])
 }