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
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))
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)))
}