From: Benjamin Auder Date: Tue, 14 Mar 2017 12:09:07 +0000 (+0100) Subject: Bug fixed: package OK X-Git-Url: https://git.auder.net/doc/html/%7B%7B%20asset%28%27mixstore/css/%7B%7B?a=commitdiff_plain;h=e0154a59e55143dac0fbd2a4739a3509bc958e76;p=epclust.git Bug fixed: package OK --- diff --git a/epclust/R/clustering.R b/epclust/R/clustering.R index 3e7fd38..886bfbc 100644 --- a/epclust/R/clustering.R +++ b/epclust/R/clustering.R @@ -26,7 +26,7 @@ clusteringTask1 <- function(indices, getContribs, K1, algoClust1, nb_items_clust ncores_clust=3, verbose=FALSE, parll=TRUE) { if (verbose) - cat(paste("*** Clustering task 1 on ",length(indices)," series\n", sep="")) + cat(paste("*** Clustering task 1 on ",length(indices)," series [start]\n", sep="")) if (length(indices) <= K1) return (indices) @@ -62,8 +62,7 @@ clusteringTask1 <- function(indices, getContribs, K1, algoClust1, nb_items_clust } if (verbose) { - cat(paste("*** [iterated] Clustering task 1: now ", - length(indices)," medoids\n", sep="")) + cat(paste("*** Clustering task 1 on ",length(indices)," medoids [iter]\n", sep="")) } } if (parll) diff --git a/epclust/R/computeWerDists.R b/epclust/R/computeWerDists.R index 8eb755c..4dbcb7b 100644 --- a/epclust/R/computeWerDists.R +++ b/epclust/R/computeWerDists.R @@ -27,10 +27,13 @@ computeWerDists <- function(indices, getSeries, nb_series_per_chunk, smooth_lvl, cwt_file <- tempfile(pattern="epclust_cwt.bin_") # Compute the getSeries(indices) CWT, and store the results in the binary file - computeSaveCWT <- function(indices) + computeSaveCWT <- function(inds) { + if (verbose) + cat(" Compute save CWT on ",length(inds)," indices\n", sep="") + # Obtain CWT as big vectors of real part + imaginary part (concatenate) - ts_cwt <- sapply(indices, function(i) { + ts_cwt <- sapply(inds, function(i) { ts <- scale(ts(getSeries(i)), center=TRUE, scale=FALSE) ts_cwt <- Rwave::cwt(ts, noctave, nvoice, w0=2*pi, twoD=TRUE, plot=FALSE) c( as.double(Re(ts_cwt)),as.double(Im(ts_cwt)) ) @@ -60,7 +63,7 @@ computeWerDists <- function(indices, getSeries, nb_series_per_chunk, smooth_lvl, Xwer_dist <- bigmemory::attach.big.matrix(Xwer_dist_desc) } - if (verbose && !parll) + if (verbose) cat(paste(" Distances from ",i," to ",i+1,"...",n,"\n", sep="")) # Get CWT of column i, and run computations for columns j>i @@ -87,10 +90,10 @@ computeWerDists <- function(indices, getSeries, nb_series_per_chunk, smooth_lvl, cat(paste("--- Precompute and serialize synchrones CWT\n", sep="")) # Split indices by packets of length at most nb_cwt_per_chunk - indices_cwt <- .splitIndices(seq_len(n), nb_cwt_per_chunk) + indices_cwt <- .splitIndices(indices, nb_cwt_per_chunk) # NOTE: next loop could potentially be run in //. Indices would be permuted (by # serialization order), and synchronicity would be required because of concurrent - # writes. Probably not worth the effort - but possible to gain some bits of speed. + # writes. Probably not worth the effort - but possible. for (inds in indices_cwt) computeSaveCWT(inds) diff --git a/epclust/R/main.R b/epclust/R/main.R index e3fa807..fe78e63 100644 --- a/epclust/R/main.R +++ b/epclust/R/main.R @@ -67,11 +67,10 @@ #' @param ncores_tasks Number of parallel tasks ('1' == sequential tasks) #' @param ncores_clust Number of parallel clusterings in one task #' @param sep Separator in CSV input file (if any provided) -#' @param nbytes Number of bytes to serialize a floating-point number: 4 or 8 +#' @param nbytes 4 or 8 bytes to (de)serialize a floating-point number #' @param endian Endianness for (de)serialization: "little" or "big" #' @param verbose FALSE: nothing printed; TRUE: some execution traces #' @param parll TRUE: run in parallel. FALSE: run sequentially -#' @param reuse_bin Re-use previously stored binary series and contributions #' #' @return A list: #' \itemize{ @@ -88,6 +87,7 @@ #' @examples #' \dontrun{ #' # WER distances computations are too long for CRAN (for now) +#' parll = FALSE #on this small example, sequential run is faster #' #' # Random series around cos(x,2x,3x)/sin(x,2x,3x) #' x <- seq(0,50,0.05) @@ -100,12 +100,13 @@ #' permut <- (0:239)%%6 * 40 + (0:239)%/%6 + 1 #' series = series[,permut] #' #dim(series) #c(240,1001) -#' res_ascii <- claws(series, K1=30, K2=6, 100, random=FALSE, verbose=TRUE) +#' res_ascii <- claws(series, K1=30, K2=6, nb_series_per_chunk=500, +#' nb_items_clust=100, random=FALSE, verbose=TRUE, parll=parll) #' #' # Same example, from CSV file #' csv_file <- tempfile(pattern="epclust_series.csv_") #' write.table(t(series), csv_file, sep=",", row.names=FALSE, col.names=FALSE) -#' res_csv <- claws(csv_file, K1=30, K2=6, 100, random=FALSE) +#' res_csv <- claws(csv_file, 30, 6, 500, 100, random=FALSE, parll=parll) #' #' # Same example, from binary file #' bin_file <- tempfile(pattern="epclust_series.bin_") @@ -113,7 +114,7 @@ #' endian <- "little" #' binarize(csv_file, bin_file, 500, ",", nbytes, endian) #' getSeries <- function(indices) getDataInFile(indices, bin_file, nbytes, endian) -#' res_bin <- claws(getSeries, K1=30, K2=6, 100, random=FALSE) +#' res_bin <- claws(getSeries, 30, 6, 500, 100, random=FALSE, parll=parll) #' unlink(csv_file) #' unlink(bin_file) #' @@ -133,6 +134,9 @@ #' serie_length <- as.integer( dbGetQuery(series_db, #' paste("SELECT COUNT(*) FROM times_values WHERE id == ",indexToID_inDB[1],sep="")) ) #' getSeries <- function(indices) { +#' indices = indices[ indices <= length(indexToID_inDB) ] +#' if (length(indices) == 0) +#' return (NULL) #' request <- "SELECT id,value FROM times_values WHERE id in (" #' for (i in seq_along(indices)) { #' request <- paste(request, indexToID_inDB[ indices[i] ], sep="") @@ -141,13 +145,9 @@ #' } #' request <- paste(request, ")", sep="") #' df_series <- dbGetQuery(series_db, request) -#' if (nrow(df_series) >= 1) -#' matrix(df_series[,"value"], nrow=serie_length) -#' else -#' NULL +#' matrix(df_series[,"value"], nrow=serie_length) #' } -#' # reuse_bin==FALSE: DB do not garantee ordering -#' res_db <- claws(getSeries, K1=30, K2=6, 100, random=FALSE, reuse_bin=FALSE) +#' res_db <- claws(getSeries, 30, 6, 500, 100, random=FALSE, parll=parll) #' dbDisconnect(series_db) #' #' # All results should be equal: @@ -156,18 +156,13 @@ #' & res_ascii$ranks == res_db$ranks) #' } #' @export -claws <- function(series, K1, K2, nb_series_per_chunk, nb_items_clust=7*K1, +claws <- function(series, K1, K2, nb_series_per_chunk, nb_items_clust=5*K1, algoClust1=function(data,K) cluster::pam(t(data),K,diss=FALSE,pamonce=1)$id.med, algoClust2=function(dists,K) cluster::pam(dists,K,diss=TRUE,pamonce=1)$id.med, wav_filt="d8", contrib_type="absolute", WER="end", smooth_lvl=3, nvoice=4, random=TRUE, ntasks=1, ncores_tasks=1, ncores_clust=3, sep=",", nbytes=4, - endian=.Platform$endian, verbose=FALSE, parll=TRUE, reuse_bin=TRUE) + endian=.Platform$endian, verbose=FALSE, parll=TRUE) { - - -#TODO: comprendre differences.......... debuguer getSeries for DB - - # Check/transform arguments if (!is.matrix(series) && !bigmemory::is.big.matrix(series) && !is.function(series) @@ -206,11 +201,8 @@ claws <- function(series, K1, K2, nb_series_per_chunk, nb_items_clust=7*K1, if (verbose) cat("...Serialize time-series (or retrieve past binary file)\n") series_file <- ".series.epclust.bin" - if (!file.exists(series_file) || !reuse_bin) - { - unlink(series_file,) + if (!file.exists(series_file)) binarize(series, series_file, nb_series_per_chunk, sep, nbytes, endian) - } getSeries <- function(inds) getDataInFile(inds, series_file, nbytes, endian) } else @@ -220,9 +212,8 @@ claws <- function(series, K1, K2, nb_series_per_chunk, nb_items_clust=7*K1, contribs_file <- ".contribs.epclust.bin" if (verbose) cat("...Compute contributions and serialize them (or retrieve past binary file)\n") - if (!file.exists(contribs_file) || !reuse_bin) + if (!file.exists(contribs_file)) { - unlink(contribs_file,) nb_curves <- binarizeTransform(getSeries, function(curves) curvesToContribs(curves, wav_filt, contrib_type), contribs_file, nb_series_per_chunk, nbytes, endian)