export vars to nodes

diff --git a/epclust/R/clustering.R b/epclust/R/clustering.R
index 42e894c..578b2f3 100644 (file)
--- a/epclust/R/clustering.R
+++ b/epclust/R/clustering.R
@@ -1,20 +1,19 @@
 # Cluster one full task (nb_curves / ntasks series)
-clusteringTask = function(K1, K2, WER, nb_series_per_chunk, indices_tasks, ncores_clust)
+clusteringTask = function(indices_clust)
 {
        cl_clust = parallel::makeCluster(ncores_clust)
-       #parallel::clusterExport(cl=cl_clust, varlist=c("fonctions_du_package"), envir=environment())
-       indices_clust = indices_task[[i]]
+       parallel::clusterExport(cl_clust,
+               varlist=c("K1","K2","WER"),
+               envir=environment())
        repeat
        {
                nb_workers = max( 1, round( length(indices_clust) / nb_series_per_chunk ) )
-               indices_workers = list()
-               for (i in 1:nb_workers)
-               {
+               indices_workers = lapply(seq_len(nb_workers), function(i) {
                        upper_bound = ifelse( i<nb_workers,
                                min(nb_series_per_chunk*i,length(indices_clust)), length(indices_clust) )
-                       indices_workers[[i]] = indices_clust[(nb_series_per_chunk*(i-1)+1):upper_bound]
-               }
-               indices_clust = parallel::parLapply(cl, indices_workers, clusterChunk, K1, K2*(WER=="mix"))
+                       indices_clust[(nb_series_per_chunk*(i-1)+1):upper_bound]
+               })
+               indices_clust = parallel::parLapply(cl, indices_workers, clusterChunk)
                # TODO: soft condition between K2 and K1, before applying final WER step
                if ((WER=="end" && length(indices_clust)==K1) || (WER=="mix" && length(indices_clust)==K2))
                        break
@@ -24,17 +23,17 @@ clusteringTask = function(K1, K2, WER, nb_series_per_chunk, indices_tasks, ncore
 }
 
 # Cluster a chunk of series inside one task (~max nb_series_per_chunk)
-clusterChunk = function(indices, K1, K2)
+clusterChunk = function(indices_chunk)
 {
-       coeffs = getCoeffs(indices)
+       coeffs = readCoeffs(indices_chunk)
        cl = computeClusters(as.matrix(coeffs[,2:ncol(coeffs)]), K1, diss=FALSE)
-       if (K2 > 0)
+       if (WER=="mix" > 0)
        {
                curves = computeSynchrones(cl)
                dists = computeWerDists(curves)
                cl = computeClusters(dists, K2, diss=TRUE)
        }
-       indices[cl]
+       indices_chunk[cl]
 }
 
 # Apply the clustering algorithm (PAM) on a coeffs or distances matrix

diff --git a/epclust/R/main.R b/epclust/R/main.R
index f5ad81a..75041a4 100644 (file)
--- a/epclust/R/main.R
+++ b/epclust/R/main.R
@@ -67,8 +67,7 @@ epclust = function(data, K1, K2, ntasks=1, nb_series_per_chunk=50*K1, min_series
                stop("WER takes values in {'end','mix'}")
 
        # Serialize all wavelets coefficients (+ IDs) onto a file
-       coeffs_file = ".coeffs"
-       ids_files = ".ids"
+       unlink(".coeffs")
        index = 1
        nb_curves = 0
        nb_coeffs = NA
@@ -77,7 +76,7 @@ epclust = function(data, K1, K2, ntasks=1, nb_series_per_chunk=50*K1, min_series
                coeffs_chunk = computeCoeffs(data, index, nb_series_per_chunk, wf)
                if (is.null(coeffs_chunk))
                        break
-               serialize(coeffs_chunk, coeffs_file, append=TRUE)
+               writeCoeffs(coeffs_chunk)
                index = index + nb_series_per_chunk
                nb_curves = nb_curves + nrow(coeffs_chunk)
                if (is.na(nb_coeffs))
@@ -91,22 +90,21 @@ epclust = function(data, K1, K2, ntasks=1, nb_series_per_chunk=50*K1, min_series
                stop("Too many tasks: less series in one task than min_series_per_chunk!")
 
        # Cluster coefficients in parallel (by nb_series_per_chunk)
-       indices = if (random) sample(nb_curves) else seq_len(nb_curves) #all indices
-       indices_tasks = list() #indices to be processed in each task
-       for (i in seq_len(ntasks))
-       {
+       indices = if (random) sample(nb_curves) else seq_len(nb_curves)
+       indices_tasks = lapply(seq_len(ntasks), function(i) {
                upper_bound = ifelse( i<ntasks, min(nb_series_per_task*i,nb_curves), nb_curves )
-               indices_task[[i]] = indices[((i-1)*nb_series_per_task+1):upper_bound]
-       }
+               indices[((i-1)*nb_series_per_task+1):upper_bound]
+       })
        library(parallel, quietly=TRUE)
        cl_tasks = parallel::makeCluster(ncores_tasks)
-       #parallel::clusterExport(cl=cl_tasks, varlist=c("ncores_clust", ...), envir=environment())
-       indices = parallel::parLapply(cl_tasks, indices_tasks, clusteringStep12, )
+       parallel::clusterExport(cl_tasks,
+               varlist=c("K1","K2","WER","nb_series_per_chunk","ncores_clust"),#TODO: pass also
+                                               #nb_coeffs...and filename (in a list... ?)
+               envir=environment())
+       indices = parallel::parLapply(cl_tasks, indices_tasks, clusteringTask)
        parallel::stopCluster(cl_tasks)
 
-##TODO: passer data ?!
-
        # Run step1+2 step on resulting ranks
-       ranks = clusteringStep12()
-       return (list("ranks"=ranks, "medoids"=getSeries(data, ranks)))
+       indices = clusterChunk(indices, K1, K2)
+       return (list("indices"=indices, "medoids"=getSeries(data, indices)))
 }

diff --git a/epclust/R/utils.R b/epclust/R/utils.R
index 347c2c6..e0f25ec 100644 (file)
--- a/epclust/R/utils.R
+++ b/epclust/R/utils.R
@@ -10,8 +10,9 @@ toInteger <- function(x, condition)
        x
 }
 
-serialize = function(coeffs, file, append)
+writeCoeffs = function(coeffs)
 {
+       file = ".coeffs"
        #.........
        #C function (from data.frame, type of IDs ??! force integers ? [yes])
        #return raw vector
@@ -19,9 +20,10 @@ serialize = function(coeffs, file, append)
 #TODO: appendCoeffs() en C --> serialize et append to file
 }
 
-deserialize = function(file, range, ncoefs)
+readCoeffs = function(indices)
 {
        #......
+       file = ".coeffs"
        #C function (from file name)
 }
 
@@ -29,8 +31,3 @@ getSeries(data, rank=NULL, id=NULL)
 {
        #TODO:
 }
-
-getCoeffs(.....) #FROM BINARY FILE !!!
-{
-
-}