3 #' Compute the synchrones curves (sum of clusters elements) from a matrix of medoids,
4 #' using euclidian distance.
6 #' @param medoids matrix of medoids in columns (curves of same length as the series)
7 #' @param getSeries Function to retrieve series (argument: 'indices', integer vector)
8 #' @param nb_curves How many series? (this is known, at this stage)
9 #' @inheritParams claws
11 #' @return A matrix of K synchrones in columns (same length as the series)
14 computeSynchrones <- function(medoids, getSeries, nb_curves,
15 nb_series_per_chunk, ncores_clust=1,verbose=FALSE,parll=TRUE)
17 # Synchrones computation is embarassingly parallel: compute it by chunks of series
18 computeSynchronesChunk <- function(indices)
22 require("bigmemory", quietly=TRUE)
23 requireNamespace("synchronicity", quietly=TRUE)
24 require("epclust", quietly=TRUE)
25 # The big.matrix objects need to be attached to be usable on the workers
26 synchrones <- bigmemory::attach.big.matrix(synchrones_desc)
27 medoids <- bigmemory::attach.big.matrix(medoids_desc)
28 m <- synchronicity::attach.mutex(m_desc)
31 # Obtain a chunk of reference series
32 series_chunk <- getSeries(indices)
33 nb_series_chunk <- ncol(series_chunk)
35 # Get medoids indices for this chunk of series
36 mi <- assignMedoids(series_chunk, medoids[,])
38 # Update synchrones using mi above, grouping it by values of mi (in 1...K)
39 # to avoid too many lock/unlock
42 # lock / unlock required because several writes at the same time
44 synchronicity::lock(m)
45 synchrones[,i] <- synchrones[,i] + rowSums(as.matrix(series_chunk[,mi==i]))
47 synchronicity::unlock(m)
54 # Use bigmemory (shared==TRUE by default) + synchronicity to fill synchrones in //
55 synchrones <- bigmemory::big.matrix(nrow=L, ncol=K, type="double", init=0.)
56 # NOTE: synchronicity is only for Linux & MacOS; on Windows: run sequentially
57 parll <- (parll && requireNamespace("synchronicity",quietly=TRUE)
58 && Sys.info()['sysname'] != "Windows")
61 m <- synchronicity::boost.mutex() #for lock/unlock, see computeSynchronesChunk
62 # mutex and big.matrix objects cannot be passed directly:
63 # they will be accessed from their description
64 m_desc <- synchronicity::describe(m)
65 synchrones_desc <- bigmemory::describe(synchrones)
66 medoids <- bigmemory::as.big.matrix(medoids)
67 medoids_desc <- bigmemory::describe(medoids)
68 # outfile=="" to see stderr/stdout on terminal
69 cl <- parallel::makeCluster(ncores_clust, outfile="")
70 parallel::clusterExport(cl, envir=environment(),
71 varlist=c("synchrones_desc","m_desc","medoids_desc","getSeries"))
75 cat(paste("--- Compute ",K," synchrones with ",nb_curves," series\n", sep=""))
77 # Balance tasks by splitting 1:nb_curves into groups of size <= nb_series_per_chunk
78 indices_workers <- .splitIndices(seq_len(nb_curves), nb_series_per_chunk)
81 parallel::parLapply(cl, indices_workers, computeSynchronesChunk)
83 lapply(indices_workers, computeSynchronesChunk)
86 parallel::stopCluster(cl)
88 return (synchrones[,])