'update'

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

diff --git a/epclust/R/computeSynchrones.R b/epclust/R/computeSynchrones.R
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+++ b/epclust/R/computeSynchrones.R
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+#' computeSynchrones
+#'
+#' Compute the synchrones curves (sum of clusters elements) from a matrix of medoids,
+#' using euclidian distance.
+#'
+#' @param medoids matrix of medoids in columns (curves of same length as the series)
+#' @param getSeries Function to retrieve series (argument: 'indices', integer vector)
+#' @param nb_curves How many series? (this is known, at this stage)
+#' @inheritParams claws
+#'
+#' @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=1,verbose=FALSE,parll=TRUE)
+{
+       # Synchrones computation is embarassingly parallel: compute it by chunks of series
+       computeSynchronesChunk = function(indices)
+       {
+               if (parll)
+               {
+                       require("bigmemory", quietly=TRUE)
+                       requireNamespace("synchronicity", quietly=TRUE)
+                       require("epclust", 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)
+
+               # Get medoids indices for this chunk of series
+               for (i in seq_len(nb_series_chunk))
+                       mi[i] <- which.min( colSums( sweep(medoids, 1, series_chunk[,i], '-')^2 ) )
+
+               # Update synchrones using mi above, grouping it by values of mi (in 1...K)
+               # to avoid too many lock/unlock
+               for (i in seq_len(K))
+               {
+                       # lock / unlock required because several writes at the same time
+                       if (parll)
+                               synchronicity::lock(m)
+                       synchrones[,i] = synchrones[,i] + rowSums(series_chunk[,mi==i])
+                       if (parll)
+                               synchronicity::unlock(m)
+               }
+               NULL
+       }
+
+       K = ncol(medoids)
+       L = nrow(medoids)
+       # 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)
+               && 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)
+               cl = parallel::makeCluster(ncores_clust)
+               parallel::clusterExport(cl, envir=environment(),
+                       varlist=c("synchrones_desc","m_desc","medoids_desc","getRefSeries"))
+       }
+
+       if (verbose)
+               cat(paste("--- Compute ",K," synchrones with ",nb_curves," series\n", sep=""))
+
+       # Balance tasks by splitting 1:nb_ref_curves into groups of size <= nb_series_per_chunk
+       indices_workers = .splitIndices(seq_len(nb_ref_curves), nb_series_per_chunk)
+       ignored <-
+               if (parll)
+                       parallel::parLapply(cl, indices_workers, computeSynchronesChunk)
+               else
+                       lapply(indices_workers, computeSynchronesChunk)
+
+       if (parll)
+               parallel::stopCluster(cl)
+
+       return (synchrones[,])
+}