X-Git-Url: https://git.auder.net/?a=blobdiff_plain;f=epclust%2FR%2Fde_serialize.R;h=cb964b6c1a83492bc5cd287939bedda9900518e3;hb=3fb6e823601002c44ffbf913e83c8d24cfa1e819;hp=5a9dd1f236b055a69777e3ff5a3ab18f94007fc7;hpb=d9bb53c5e1392018bf67f92140edb10137f3423c;p=epclust.git

diff --git a/epclust/R/de_serialize.R b/epclust/R/de_serialize.R
index 5a9dd1f..cb964b6 100644
--- a/epclust/R/de_serialize.R
+++ b/epclust/R/de_serialize.R
@@ -1,61 +1,61 @@
-#' @name de_serialize
-#' @rdname de_serialize
-#' @aliases binarize binarizeTransform getDataInFile
+#' (De)Serialization of a [big]matrix or data stream
 #'
-#' @title (De)Serialization of a [big]matrix or data stream
+#' \code{binarize()} serializes a matrix or CSV file with minimal overhead, into a
+#' binary file. \code{getDataInFile()} achieves the inverse task: she retrieves (ASCII)
+#' data rows from indices in the binary file. Finally, \code{binarizeTransform()}
+#' serialize transformations of all data chunks. To use it a data-retrieval function
+#' must be provided -- thus \code{binarize} will most likely be used first
+#' (and then a function defined to seek in generated binary file)
 #'
-#' @description \code{binarize()} serializes a matrix or CSV file with minimal overhead,
-#'   into a binary file. \code{getDataInFile()} achieves the inverse task: she retrieves
-#'   (ASCII) data rows from indices in the binary file. Finally,
-#'   \code{binarizeTransform()} serialize transformations of all data chunks; to use it,
-#'   a data-retrieval function must be provided, thus \code{binarize} will most likely be
-#'   used first (and then a function defined to seek in generated binary file)
-#'
-#' @param data_ascii Either a matrix or CSV file, with items in rows
-#' @param indices Indices of the lines to retrieve
-#' @param data_bin_file Name of binary file on output (\code{binarize})
-#'   or input (\code{getDataInFile})
-#' @param nb_per_chunk Number of lines to process in one batch (big.matrix or connection)
-#' @inheritParams claws
+#' @param data_ascii Matrix (by columns) or CSV file or connection (by rows)
+#' @param data_bin_file Name of binary file on output of \code{binarize()}
+#'   or input of \code{getDataInFile()}
+#' @param nb_per_chunk Number of lines to process in one batch
 #' @param getData Function to retrieve data chunks
 #' @param transform Transformation function to apply on data chunks
+#' @param indices Indices of the lines to retrieve
+#' @inheritParams claws
+#'
+#' @return For \code{getDataInFile()}, a matrix with columns corresponding to the
+#'   requested indices. \code{binarizeTransform()} returns the number of processed lines.
+#'   \code{binarize()} is designed to serialize in several calls, thus returns nothing.
 #'
-#' @return For \code{getDataInFile()}, the matrix with rows corresponding to the
-#'   requested indices. \code{binarizeTransform} returns the number of processed lines.
-#'   \code{binarize} is designed to serialize in several calls, thus returns nothing.
+#' @name de_serialize
+#' @rdname de_serialize
+#' @aliases binarize binarizeTransform getDataInFile
 NULL
 
 #' @rdname de_serialize
 #' @export
-binarize = function(data_ascii, data_bin_file, nb_per_chunk,
+binarize <- function(data_ascii, data_bin_file, nb_per_chunk,
 	sep=",", nbytes=4, endian=.Platform$endian)
 {
 	# data_ascii can be of two types: [big.]matrix, or connection
 	if (is.character(data_ascii))
-		data_ascii = file(data_ascii, open="r")
+		data_ascii <- file(data_ascii, open="r")
 	else if (methods::is(data_ascii,"connection") && !isOpen(data_ascii))
 		open(data_ascii)
-	is_matrix = !methods::is(data_ascii,"connection")
+	is_matrix <- !methods::is(data_ascii,"connection")
 
 	# At first call, the length of a stored row is written. So it's important to determine
 	# if the serialization process already started.
-	first_write = (!file.exists(data_bin_file) || file.info(data_bin_file)$size == 0)
+	first_write <- (!file.exists(data_bin_file) || file.info(data_bin_file)$size == 0)
 
 	# Open the binary file for writing (or 'append' if already exists)
-	data_bin = file(data_bin_file, open=ifelse(first_write,"wb","ab"))
+	data_bin <- file(data_bin_file, open=ifelse(first_write,"wb","ab"))
 
 	if (first_write)
 	{
 		# Write data length on first call: number of items always on 8 bytes
 		writeBin(0L, data_bin, size=8, endian=endian)
 		if (is_matrix)
-			data_length = nrow(data_ascii)
+			data_length <- nrow(data_ascii)
 		else #connection
 		{
 			# Read the first line to know data length, and write it then
-			data_line = scan(data_ascii, double(), sep=sep, nlines=1, quiet=TRUE)
+			data_line <- scan(data_ascii, double(), sep=sep, nlines=1, quiet=TRUE)
 			writeBin(data_line, data_bin, size=nbytes, endian=endian)
-			data_length = length(data_line)
+			data_length <- length(data_line)
 		}
 	}
 
@@ -63,21 +63,21 @@ binarize = function(data_ascii, data_bin_file, nb_per_chunk,
 	{
 		# Data is processed by chunks; although this may not be so useful for (normal) matrix
 		# input, it could for a file-backed big.matrix. It's easier to follow a unified pattern.
-		index = 1
+		index <- 1
 	}
 	repeat
 	{
 		if (is_matrix)
 		{
-			data_chunk =
+			data_chunk <-
 				if (index <= ncol(data_ascii))
 					as.double(data_ascii[,index:min(ncol(data_ascii),index+nb_per_chunk-1)])
 				else
 					double(0)
-			index = index + nb_per_chunk
+			index <- index + nb_per_chunk
 		}
 		else #connection
-			data_chunk = scan(data_ascii, double(), sep=sep, nlines=nb_per_chunk, quiet=TRUE)
+			data_chunk <- scan(data_ascii, double(), sep=sep, nlines=nb_per_chunk, quiet=TRUE)
 
 		# Data size is unknown in the case of a connection
 		if (length(data_chunk)==0)
@@ -89,8 +89,8 @@ binarize = function(data_ascii, data_bin_file, nb_per_chunk,
 
 	if (first_write)
 	{
-		# Write data_length, = (file_size-1) / (nbytes*nbWritten) at offset 0 in data_bin
-		ignored = seek(data_bin, 0)
+		# Write data_length, == (file_size-1) / (nbytes*nbWritten) at offset 0 in data_bin
+		ignored <- seek(data_bin, 0)
 		writeBin(data_length, data_bin, size=8, endian=endian)
 	}
 	close(data_bin)
@@ -101,47 +101,47 @@ binarize = function(data_ascii, data_bin_file, nb_per_chunk,
 
 #' @rdname de_serialize
 #' @export
-binarizeTransform = function(getData, transform, data_bin_file, nb_per_chunk,
+binarizeTransform <- function(getData, transform, data_bin_file, nb_per_chunk,
 	nbytes=4, endian=.Platform$endian)
 {
-	nb_items = 0 #side-effect: store the number of transformed items
-	index = 1
+	nb_items <- 0 #side-effect: store the number of transformed items
+	index <- 1
 	repeat
 	{
 		# Retrieve a chunk of data in a binary file (generally obtained by binarize())
-		data_chunk = getData((index-1)+seq_len(nb_per_chunk))
+		data_chunk <- getData((index-1)+seq_len(nb_per_chunk))
 		if (is.null(data_chunk))
 			break
 
 		# Apply transformation on the current chunk (by columns)
-		transformed_chunk = transform(data_chunk)
+		transformed_chunk <- transform(data_chunk)
 
 		# Save the result in binary format
 		binarize(transformed_chunk, data_bin_file, nb_per_chunk, ",", nbytes, endian)
 
-		index = index + nb_per_chunk
-		nb_items = nb_items + nrow(data_chunk)
+		index <- index + nb_per_chunk
+		nb_items <- nb_items + ncol(data_chunk)
 	}
 	nb_items #number of transformed items
 }
 
 #' @rdname de_serialize
 #' @export
-getDataInFile = function(indices, data_bin_file, nbytes=4, endian=.Platform$endian)
+getDataInFile <- function(indices, data_bin_file, nbytes=4, endian=.Platform$endian)
 {
-	data_bin = file(data_bin_file, "rb") #source binary file
+	data_bin <- file(data_bin_file, "rb") #source binary file
 
-	data_size = file.info(data_bin_file)$size #number of bytes in the file
+	data_size <- file.info(data_bin_file)$size #number of bytes in the file
 	# data_length: length of a vector in the binary file (first element, 8 bytes)
-	data_length = readBin(data_bin, "integer", n=1, size=8, endian=endian)
+	data_length <- readBin(data_bin, "integer", n=1, size=8, endian=endian)
 
 	# Seek all 'indices' columns in the binary file, using data_length and nbytes
 	# to compute the offset ( index i at 8 + i*data_length*nbytes )
-	data_ascii = do.call( cbind, lapply( indices, function(i) {
-		offset = 8+(i-1)*data_length*nbytes
-		if (offset > data_size)
+	data_ascii <- do.call( cbind, lapply( indices, function(i) {
+		offset <- 8+(i-1)*data_length*nbytes
+		if (offset >= data_size)
 			return (NULL)
-		ignored = seek(data_bin, offset) #position cursor at computed offset
+		ignored <- seek(data_bin, offset) #position cursor at computed offset
 		readBin(data_bin, "double", n=data_length, size=nbytes, endian=endian)
 	} ) )
 	close(data_bin)