X-Git-Url: https://git.auder.net/?p=epclust.git;a=blobdiff_plain;f=pkg%2FR%2Fde_serialize.R;fp=pkg%2FR%2Fde_serialize.R;h=cb964b6c1a83492bc5cd287939bedda9900518e3;hp=0000000000000000000000000000000000000000;hb=e906736ea27105237e84c904dce6170353726292;hpb=57f337af19cd6251815bb1ff2d62f4c58e8b6078

diff --git a/pkg/R/de_serialize.R b/pkg/R/de_serialize.R
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+#' (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)
+#'
+#' @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.
+#'
+#' @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,
+	sep=",", nbytes=4, endian=.Platform$endian)
+{
+	# data_ascii can be of two types: [big.]matrix, or connection
+	if (is.character(data_ascii))
+		data_ascii <- file(data_ascii, open="r")
+	else if (methods::is(data_ascii,"connection") && !isOpen(data_ascii))
+		open(data_ascii)
+	is_matrix <- !methods::is(data_ascii,"connection")
+
+	# At first call, the length of a stored row is written. So it's important to determine
+	# if the serialization process already started.
+	first_write <- (!file.exists(data_bin_file) || file.info(data_bin_file)$size == 0)
+
+	# Open the binary file for writing (or 'append' if already exists)
+	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)
+		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)
+			writeBin(data_line, data_bin, size=nbytes, endian=endian)
+			data_length <- length(data_line)
+		}
+	}
+
+	if (is_matrix)
+	{
+		# 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
+	}
+	repeat
+	{
+		if (is_matrix)
+		{
+			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
+		}
+		else #connection
+			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)
+			break
+
+		# Write this chunk of data to the binary file
+		writeBin(data_chunk, data_bin, size=nbytes, endian=endian)
+	}
+
+	if (first_write)
+	{
+		# 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)
+
+	if ( ! is_matrix )
+		close(data_ascii)
+}
+
+#' @rdname de_serialize
+#' @export
+binarizeTransform <- function(getData, transform, data_bin_file, nb_per_chunk,
+	nbytes=4, endian=.Platform$endian)
+{
+	nb_items <- 0 #side-effect: store the number of transformed items
+	index <- 1
+	repeat
+	{
+		# Retrieve a chunk of data in a binary file (generally obtained by binarize())
+		data_chunk <- getData((index-1)+seq_len(nb_per_chunk))
+		if (is.null(data_chunk))
+			break
+
+		# Apply transformation on the current chunk (by columns)
+		transformed_chunk <- transform(data_chunk)
+
+		# Save the result in binary format
+		binarize(transformed_chunk, data_bin_file, nb_per_chunk, ",", nbytes, endian)
+
+		index <- index + nb_per_chunk
+		nb_items <- nb_items + ncol(data_chunk)
+	}
+	nb_items #number of transformed items
+}
+
+#' @rdname de_serialize
+#' @export
+getDataInFile <- function(indices, data_bin_file, nbytes=4, endian=.Platform$endian)
+{
+	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_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)
+
+	# 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)
+			return (NULL)
+		ignored <- seek(data_bin, offset) #position cursor at computed offset
+		readBin(data_bin, "double", n=data_length, size=nbytes, endian=endian)
+	} ) )
+	close(data_bin)
+
+	data_ascii #retrieved data, in columns
+}