improvements

[epclust.git] / epclust / R / main.R

diff --git a/epclust/R/main.R b/epclust/R/main.R
index bba0618..977e61b 100644 (file)
--- a/epclust/R/main.R
+++ b/epclust/R/main.R
@@ -7,8 +7,9 @@
 #' @param getSeries Access to the (time-)series, which can be of one of the three
 #'   following types:
 #'   \itemize{
-#'     \item matrix: each line contains all the values for one time-serie, ordered by time
-#'     \item connection: any R connection object (e.g. a file) providing lines as described above
+#'     \item [big.]matrix: each line contains all the values for one time-serie, ordered by time
+#'     \item connection: any R connection object providing lines as described above
+#'     \item character: name of a CSV file containing series in rows (no header)
 #'     \item function: a custom way to retrieve the curves; it has only one argument:
 #'       the indices of the series to be retrieved. See examples
 #'   }
@@ -32,7 +33,7 @@
 #' @param verbose Level of verbosity (0/FALSE for nothing or 1/TRUE for all; devel stage)
 #' @param parll TRUE to fully parallelize; otherwise run sequentially (debug, comparison)
 #'
-#' @return A matrix of the final medoids curves (K2) in rows
+#' @return A big.matrix of the final medoids curves (K2) in rows
 #'
 #' @examples
 #' \dontrun{
@@ -144,7 +145,7 @@ claws = function(getSeries, K1, K2,
                getSeries = function(inds) getDataInFile(inds, series_file, nbytes, endian)
        }
 
-       # Serialize all computed wavelets contributions onto a file
+       # Serialize all computed wavelets contributions into a file
        contribs_file = paste(bin_dir,"contribs",sep="") ; unlink(contribs_file)
        index = 1
        nb_curves = 0
@@ -163,13 +164,14 @@ claws = function(getSeries, K1, K2,
 
        runTwoStepClustering = function(inds)
        {
-               if (parll)
+               if (parll && ntasks>1)
                        require("epclust", quietly=TRUE)
                indices_medoids = clusteringTask1(
                        inds, getContribs, K1, nb_series_per_chunk, ncores_clust, verbose, parll)
                if (WER=="mix")
                {
-                       medoids2 = computeClusters2(getSeries(indices_medoids),
+                       medoids1 = bigmemory::as.big.matrix( getSeries(indices_medoids) )
+                       medoids2 = clusteringTask2(medoids1,
                                K2, getSeries, nb_curves, nb_series_per_chunk, ncores_clust, verbose, parll)
                        binarize(medoids2, synchrones_file, nb_series_per_chunk, sep, nbytes, endian)
                        return (vector("integer",0))
@@ -184,25 +186,30 @@ claws = function(getSeries, K1, K2,
                indices_all[((i-1)*nb_series_per_task+1):upper_bound]
        })
        if (verbose)
-               cat(paste("...Run ",ntasks," x stage 1 in parallel\n",sep=""))
+       {
+               message = paste("...Run ",ntasks," x stage 1", sep="")
+               if (WER=="mix")
+                       message = paste(message," + stage 2", sep="")
+               cat(paste(message,"\n", sep=""))
+       }
        if (WER=="mix")
                {synchrones_file = paste(bin_dir,"synchrones",sep="") ; unlink(synchrones_file)}
-       if (parll)
+       if (parll && ntasks>1)
        {
                cl = parallel::makeCluster(ncores_tasks)
                varlist = c("getSeries","getContribs","K1","K2","verbose","parll",
-                       "nb_series_per_chunk","ncores_clust","sep","nbytes","endian")
+                       "nb_series_per_chunk","ntasks","ncores_clust","sep","nbytes","endian")
                if (WER=="mix")
                        varlist = c(varlist, "synchrones_file")
                parallel::clusterExport(cl, varlist=varlist, envir = environment())
        }
 
        # 1000*K1 indices [if WER=="end"], or empty vector [if WER=="mix"] --> series on file
-       if (parll)
+       if (parll && ntasks>1)
                indices = unlist( parallel::parLapply(cl, indices_tasks, runTwoStepClustering) )
        else
                indices = unlist( lapply(indices_tasks, runTwoStepClustering) )
-       if (parll)
+       if (parll && ntasks>1)
                parallel::stopCluster(cl)
 
        getRefSeries = getSeries
@@ -226,13 +233,14 @@ claws = function(getSeries, K1, K2,
                cat("...Run final // stage 1 + stage 2\n")
        indices_medoids = clusteringTask1(
                indices, getContribs, K1, nb_series_per_chunk, ncores_tasks*ncores_clust, verbose, parll)
-       medoids = computeClusters2(getSeries(indices_medoids), K2,
+       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)
 
        # Cleanup
        unlink(bin_dir, recursive=TRUE)
 
-       medoids
+       medoids2
 }
 
 #' curvesToContribs