epclust/R/computeSynchrones.R

   1 #' computeSynchrones
   2 #'
   3 #' Compute the synchrones curves (sums of clusters elements) from a matrix of medoids,
   4 #' using euclidian distance.
   5 #'
   6 #' @param medoids matrix of K medoids curves in columns
   7 #' @param nb_curves How many series? (this is known, at this stage)
   8 #' @inheritParams claws
   9 #' @inheritParams computeWerDists
  10 #'
  11 #' @return A matrix of K synchrones in columns (same length as the series)
  12 #'
  13 #' @export
  14 computeSynchrones <- function(medoids, getSeries, nb_curves,
  15     nb_series_per_chunk, ncores=3, verbose=FALSE, parll=TRUE)
  16 {
  17     # Synchrones computation is embarassingly parallel: compute it by chunks of series
  18     computeSynchronesChunk <- function(indices)
  19     {
  20         # Obtain a chunk of reference series
  21         series_chunk <- getSeries(indices)
  22         nb_series_chunk <- ncol(series_chunk)
  23
  24         # Get medoids indices for this chunk of series
  25         mi <- assignMedoids(series_chunk, medoids[,])
  26
  27         # Update synchrones using mi above, grouping it by values of mi (in 1...K)
  28         # to avoid too many lock/unlock
  29         for (i in seq_len(K))
  30         {
  31             # lock / unlock required because several writes at the same time
  32             if (parll)
  33                 synchronicity::lock(m)
  34             synchrones[,i] <- synchrones[,i] + rowSums(as.matrix(series_chunk[,mi==i]))
  35             if (parll)
  36                 synchronicity::unlock(m)
  37         }
  38         NULL
  39     }
  40
  41     K <- ncol(medoids)
  42     L <- nrow(medoids)
  43     # Use bigmemory (shared==TRUE by default) + synchronicity to fill synchrones in //
  44     synchrones <- bigmemory::big.matrix(nrow=L, ncol=K, type="double", init=0.)
  45     # NOTE: synchronicity is only for Linux & MacOS; on Windows: run sequentially
  46     parll <- (parll && requireNamespace("synchronicity",quietly=TRUE)
  47         && Sys.info()['sysname'] != "Windows")
  48
  49     if (parll)
  50         m <- synchronicity::boost.mutex() #for lock/unlock, see computeSynchronesChunk
  51
  52     if (verbose)
  53         cat(paste("--- Compute ",K," synchrones with ",nb_curves," series\n", sep=""))
  54
  55     # Balance tasks by splitting 1:nb_curves into groups of size <= nb_series_per_chunk
  56     indices_workers <- .splitIndices(seq_len(nb_curves), nb_series_per_chunk)
  57     ignored <-
  58         if (parll)
  59         {
  60             parallel::mclapply(indices_workers,
  61                 function(inds) computeSynchronesChunk(inds), mc.cores=ncores)
  62         }
  63         else
  64             lapply(indices_workers, computeSynchronesChunk)
  65
  66     return (synchrones[,])
  67 }