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IO.R
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IO.R
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## For specifications of FACS 3.0 see
## http://www.isac-net.org and the file
## fcs3.html in the doc directory
## ==========================================================================
## Determine which 'files' are valid FCS files
## - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
#' @export
isFCSfile <- function(files)
{
sapply(files, function(f){
if (file.exists(f)) {
con <- file(f, open="rb")
on.exit(close(con))
version <- readChar(con, 6)
isTRUE(version %in% c("FCS2.0", "FCS3.0", "FCS3.1"))
}
else FALSE
})
}
## ==========================================================================
## Reading FCS file header and TEXT section only
## - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
#' Read the TEXT section of a FCS file
#'
#' Read (part of) the TEXT section of a Data File Standard for Flow Cytometry
#' that contains FACS keywords.
#'
#' The function \code{read.FCSheader} works with the output of the FACS machine
#' software from a number of vendors (FCS 2.0, FCS 3.0 and List Mode Data LMD).
#' The output of the function is the TEXT section of the FCS files. The user
#' can specify some keywords to limit the output to the information of
#' interest.
#'
#' @name read.FCSheader
#'
#' @param files Character vector of filenames.
#' @param path Directory where to look for the files.
#' @param keyword An optional character vector that specifies the FCS keyword
#' to read.
#' @param ... other arguments passed to \code{link[flowCore]{read.FCS}}
#'
#' @return A list of character vectors. Each element of the list correspond to
#' one FCS file.
#' @author N.Le Meur
#' @seealso \code{link[flowCore]{read.flowSet}},
#' \code{link[flowCore]{read.FCS}}
#' @keywords IO
#' @examples
#'
#' samp <- read.FCSheader(system.file("extdata",
#' "0877408774.B08", package="flowCore"))
#' samp
#'
#' samp <- read.FCSheader(system.file("extdata",
#' "0877408774.B08", package="flowCore"), keyword=c("$DATE", "$FIL"))
#' samp
#'
#' @export
read.FCSheader <- function(files, path=".", keyword=NULL, ...)
{
stopifnot(is.character(files), length(files)>=1, files!="")
filenames <- files
if(path != ".")
files = file.path(path, files)
res <- lapply(files, function(file){
thisRes <- try(header(file, ...), silent = TRUE)
if(class(thisRes) == "try-error"){
stop(thisRes, file)
}else
thisRes
})
if (!is.null(keyword))
res <- lapply(res, function(x) x[keyword])
names(res) <- filenames
res
}
header <- function(files, ...){
con <- file(files, open="rb")
offsets <- findOffsets(con, ...)
txt <- readFCStext(con, offsets, ...)
close(con)
txt
}
## ==========================================================================
## main wrapper to read FCS files
## - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
#' Read an FCS file
#'
#' Check validity and Read Data File Standard for Flow Cytometry
#'
#'
#' The function \code{isFCSfile} determines whether its arguments are valid FCS
#' files.
#'
#' The function \code{read.FCS} works with the output of the FACS machine
#' software from a number of vendors (FCS 2.0, FCS 3.0 and List Mode Data LMD).
#' However, the FCS 3.0 standard includes some options that are not yet
#' implemented in this function. If you need extensions, please let me know.
#' The output of the function is an object of class \code{flowFrame}.
#'
#' For specifications of FCS 3.0 see \url{http://www.isac-net.org} and the file
#' \url{../doc/fcs3.html} in the \code{doc} directory of the package.
#'
#' The \code{which.lines} arguments allow you to read a subset of the record as
#' you might not want to read the thousands of events recorded in the FCS file.
#' It is mainly used when there is not enough memory to read one single FCS
#' (which probably will not happen). It will probably take more time than
#' reading the entire FCS (due to the multiple disk IO).
#' @name read.FCS
#' @aliases read.FCS cleanup isFCSfile
#' @usage
#' isFCSfile(files)
#'
#' read.FCS(filename, transformation="linearize", which.lines=NULL,
#' alter.names=FALSE, column.pattern=NULL, invert.pattern = FALSE,
#' decades=0, ncdf = FALSE, min.limit=NULL,
#' truncate_max_range = TRUE, dataset=NULL, emptyValue=TRUE,
#' channel_alias = NULL, ...)
#'
#' @param files A vector of filenames
#' @param filename Character of length 1: filename
#' @param transformation An character string that defines the type of
#' transformation. Valid values are \code{linearize} (default),
#' \code{linearize-with-PnG-scaling}, or \code{scale}. The \code{linearize}
#' transformation applies the appropriate power transform to the data. The
#' \code{linearize-with-PnG-scaling} transformation applies the appropriate
#' power transform for parameters stored on log scale, and also a linear
#' scaling transformation based on the 'gain' (FCS \$PnG keywords) for
#' parameters stored on a linear scale. The \code{scale} transformation scales
#' all columns to $[0,10^decades]$. defaulting to decades=0 as in the FCS4
#' specification. A logical can also be used: \code{TRUE} is equal to
#' \code{linearize} and \code{FALSE}(or \code{NULL}) corresponds to no
#' transformation. Also when the transformation keyword of the FCS header is
#' set to "custom" or "applied", no transformation will be used.
#' @param which.lines Numeric vector to specify the indices of the lines to be
#' read. If NULL all the records are read, if of length 1, a random sample of
#' the size indicated by \code{which.lines} is read in. It's used to achieve partial disk IO
#' for the large FCS that can't fit the full data into memory. Be aware the potential slow read
#' (especially for the large size of random sampling) due to the frequent disk seek operations.
#' @param alter.names boolean indicating whether or not we should rename the
#' columns to valid R names using \code{\link{make.names}}. The default is
#' FALSE.
#' @param column.pattern An optional regular expression defining parameters we
#' should keep when loading the file. The default is NULL.
#' @param invert.pattern logical. By default, \code{FALSE}. If \code{TRUE},
#' inverts the regular expression specified in \code{column.pattern}. This is
#' useful for indicating the channel names that we do not want to read. If
#' \code{column.pattern} is set to \code{NULL}, this argument is ignored.
#' @param decades When scaling is activated, the number of decades to use for
#' the output.
#' @param ncdf Deprecated. Please use 'ncdfFlow' package for cdf based storage.
#' @param min.limit The minimum value in the data range that is allowed. Some
#' instruments produce extreme artifactual values. The positive data range for
#' each parameter is completely defined by the measurement range of the
#' instrument and all larger values are set to this threshold. The lower data
#' boundary is not that well defined, since compensation might shift some
#' values below the original measurement range of the instrument. This can be
#' set to an arbitrary number or to \code{NULL} (the default value), in which
#' case the original values are kept. When the transformation keyword of the FCS header is
#' set (typically to "custom" or "applied"), no shift up to min.limit will occur.
#' @param truncate_max_range logical type. Default is TRUE. can be optionally
#' turned off to avoid truncating the extreme positive value to the instrument
#' measurement range .i.e.'$PnR'. When the transformation keyword of the FCS header is
#' set (typically to "custom" or "applied"), no truncation will occur.
#' @param dataset The FCS file specification allows for multiple data segments
#' in a single file. Since the output of \code{read.FCS} is a single
#' \code{flowFrame} we can't automatically read in all available sets. This
#' parameter allows to chose one of the subsets for import. Its value is
#' supposed to be an integer in the range of available data sets. This argument
#' is ignored if there is only a single data segment in the FCS file.
#' @param emptyValue boolean indicating whether or not we allow empty value for
#' keyword values in TEXT segment. It affects how the double delimiters are
#' treated. IF TRUE, The double delimiters are parsed as a pair of start and
#' end single delimiter for an empty value. Otherwise, double delimiters are
#' parsed one part of string as the keyword value. default is TRUE.
#' @param channel_alias an optional data.frame used to provide the alias of the channels
#' to standardize and solve the discrepancy across FCS files. It is expected to
#' contain 'alias' and 'channels' column of 'channel_alias'. Each row/entry specifies the common
#' alias name for a collection of channels (comma separated). See examples for
#' details.
#'
#' For each channel in the FCS file, read.FCS will first attempt
#' to find an exact match in the 'channels' column. If no exact match is found,
#' it will check for partial matches. That is, if "V545" is in the 'channels'
#' column of 'channel_alias' and "V545-A" is present in the FCS file, this
#' partial match will allow the corresponding 'alias' to be assigned. This partial
#' matching only works in this direction ("V545-A" in the 'channels' column will
#' not match "V545" in the FCS file) and care should be exercised to ensure no unintended
#' partial matching of other channel names. If no exact or partial match is found,
#' the channel is unchanged in the resulting \code{flowFrame}.
#'
#' @param ... ignore.text.offset: whether to ignore the keyword values in TEXT
#' segment when they don't agree with the HEADER. Default is FALSE, which
#' throws the error when such discrepancy is found. User can turn it on to
#' ignore TEXT segment when he is sure of the accuracy of HEADER so that the
#' file still can be read.
#'
#' @return
#'
#' \code{isFCSfile} returns a logical vector.
#'
#' \code{read.FCS} returns an object of class
#' \code{\link[flowCore:flowFrame-class]{flowFrame}} that contains the data in
#' the \code{exprs} slot, the parameters monitored in the \code{parameters}
#' slot and the keywords and value saved in the header of the FCS file.
#'
#' @author F. Hahne, N.Le Meur
#' @seealso \code{\link[flowCore]{read.flowSet}}
#' @keywords IO
#' @examples
#'
#' ## a sample file
#' fcsFile <- system.file("extdata", "0877408774.B08", package="flowCore")
#'
#' ## read file and linearize values
#' samp <- read.FCS(fcsFile, transformation="linearize")
#' exprs(samp[1:3,])
#' keyword(samp)[3:6]
#' class(samp)
#'
#' ## Only read in lines 2 to 5
#' subset <- read.FCS(fcsFile, which.lines=2:5, transformation="linearize")
#' exprs(subset)
#'
#' ## Read in a random sample of 100 lines
#' subset <- read.FCS(fcsFile, which.lines=100, transformation="linearize")
#' nrow(subset)
#'
#' #manually supply the alias vs channel options mapping as a data.frame
#' map <- data.frame(alias = c("A", "B")
#' , channels = c("FL2", "FL4")
#' )
#' fr <- read.FCS(fcsFile, channel_alias = map)
#' fr
#'
#' @export
read.FCS <- function(filename,
transformation="linearize",
which.lines=NULL,
alter.names=FALSE,
column.pattern=NULL,
invert.pattern = FALSE,
decades=0,
ncdf=FALSE,
min.limit=NULL,
truncate_max_range = TRUE,
dataset=NULL,
emptyValue=TRUE
, channel_alias = NULL
, ...)
{
channel_alias <- check_channel_alias(channel_alias)
if(ncdf)
.Deprecated("'ncdf' argument is deprecated!Please use 'ncdfFlow' package for disk-based data structure.")
## check file name
if(!is.character(filename) || length(filename)!=1)
stop("'filename' must be character scalar")
if(!file.exists(filename))
stop(paste("'", filename, "' is not a valid file", sep=""))
con <- file(filename, open="rb")
on.exit(close(con))
## transform or scale data?
fcsPnGtransform <- FALSE
if(is.logical(transformation) && transformation ||
!is.null(transformation) && transformation == "linearize") {
transformation <- TRUE
scale <- FALSE
} else if ( !is.null(transformation) && transformation == "scale") {
transformation <- TRUE
scale <- TRUE
} else if ( !is.null(transformation) && transformation == "linearize-with-PnG-scaling") {
transformation <- TRUE
scale <- FALSE
fcsPnGtransform <- TRUE
} else if (is.null(transformation) || is.logical(transformation) &&
!transformation) {
transformation <- FALSE
scale <- FALSE
}
## read the file
offsets <- findOffsets(con,emptyValue=emptyValue, dataset = dataset, ...)
txt <- readFCStext(con, offsets,emptyValue=emptyValue, ...)
## We only transform if the data in the FCS file hasn't already been
## transformed before
if (fcsPnGtransform) txt[["flowCore_fcsPnGtransform"]] <- "linearize-with-PnG-scaling"
if("transformation" %in% names(txt) &&
txt[["transformation"]] %in% c("applied", "custom"))
transformation <- FALSE
mat <- readFCSdata(con, offsets, txt, transformation, which.lines,
scale, alter.names, decades, min.limit, truncate_max_range, channel_alias)
matRanges <- attr(mat,"ranges")
id <- paste("$P",1:ncol(mat),sep="")
zeroVals <- as.numeric(sapply(strsplit(txt[paste(id,"E",sep="")], ","),
function(x) x[2]))
absMin <- colMins(mat,,na.rm=TRUE) # replace apply with matrixStats::colMins to speed up
# absMin <- apply(mat,2,min,na.rm=TRUE)
realMin <- pmin(zeroVals,pmax(-111, absMin, na.rm=TRUE), na.rm=TRUE)
keep_idx <- seq_along(colnames(mat))
remove_idx <- NULL
# Only keep certain parameters
if(!is.null(column.pattern)) {
n <- colnames(mat)
keep_idx <- grep(column.pattern, n, invert = invert.pattern)
remove_idx <- setdiff(seq_along(colnames(mat)), keep_idx)
cols <- names(attr(mat, "dimnames")[[2]])
mat <- mat[,keep_idx,drop=FALSE]
matRanges <- matRanges[keep_idx]
names(attr(mat, "dimnames")[[2]]) <- cols[keep_idx]
attr(mat, "ranges") <- matRanges
absMin <- absMin[keep_idx]
realMin <- realMin[keep_idx]
zeroVals <- zeroVals[keep_idx]
id <- id[keep_idx]
}
if("transformation" %in% names(txt) && txt[["transformation"]] == "custom") {
for(i in seq_along(colnames(mat))) {
realMin[i] <- as.numeric(txt[[sprintf("flowCore_$P%sRmin", keep_idx[i])]])
}
}
params <- makeFCSparameters(colnames(mat),txt, transformation, scale,
decades, realMin, id=keep_idx)
# Fill invalid/missing range values with channel maxima read from data
fix_pnr_idx <- which(is.na(params@data[, "maxRange"]))
if(length(fix_pnr_idx) > 0){
fix_pnr_vals <- matRanges[fix_pnr_idx]
params@data[fix_pnr_idx, "maxRange"] <- fix_pnr_vals
params@data[fix_pnr_idx, "range"] <- fix_pnr_vals + 1
}
## check for validity
if(is.null(which.lines)){
total_number_of_events <- as.integer(readFCSgetPar(txt, "$TOT"));
if(total_number_of_events != nrow(mat))
stop("file", filename, "seems to be corrupted. \n The actual number of cells in data section ("
, nrow(mat), ") is not consistent with keyword '$TOT' (", total_number_of_events , ")")
}
## set transformed flag and fix the PnE and the Datatype keywords
## also add our own PnR fields.
txt[["FILENAME"]] <- filename
if(transformation==TRUE) {
txt[["transformation"]] <-"applied"
for(p in seq_along(pData(params)$name)) {
txt[[sprintf("$P%sE", p)]] <- sprintf("0,%g", 0)
txt[[sprintf("flowCore_$P%sRmax", keep_idx[p])]] <- matRanges[p] +1
txt[[sprintf("flowCore_$P%sRmin", keep_idx[p])]] <- realMin[p]
}
txt[["$DATATYPE"]] <- "F"
}
## build description from FCS parameters
if(offsets["FCSversion"]<=2)
{
description <- strsplit(txt,split="\n")
names(description) <- names(txt)
}else
{
description <- strsplit(txt, split=NA) # not really splitting, but converting the data structure}
}
# Fill invalid/missing PnR values with channel maxima read from data
if(length(fix_pnr_idx) > 0)
description[paste0("$P", fix_pnr_idx, "R")] <- fix_pnr_vals + 1
# Remove keywords for removed parameters
if(!is.null(remove_idx)&&length(remove_idx)>0){
remove_regex <- paste0("\\$P", remove_idx, "[A-Z]+")
remove_keys <- lapply(remove_regex, function(rx) grep(rx, names(description), value=TRUE))
description <- description[!names(description) %in% do.call(c, remove_keys)]
}
## the spillover matrix
for(sn in .spillover_pattern){
sp <- description[[sn]]
if(!is.null(sp)){
sp <- txt2spillmatrix(sp)
if(is.matrix(sp))
{
cnames <- colnames(sp)
cnames <- update_channel_by_alias(cnames, channel_alias, silent = TRUE)
if(alter.names)
cnames <- make.names(cnames)
colnames(sp) <- cnames
description[[sn]] <- sp
}
}
}
tmp <- new("flowFrame", exprs=mat, description= description,
parameters=params)
identifier(tmp) <- basename(identifier(tmp))
return(tmp)
}
txt2spillmatrix <- function(txt, cpp = TRUE){
if(cpp)
{
string_to_spill(txt)
}else
{
splt <- strsplit(txt, ",")[[1]]
nrCols <- as.numeric(splt[1])
if(!is.na(nrCols)&&nrCols > 0)
{
cnames <- splt[2:(nrCols+1)]
vals <- as.numeric(splt[(nrCols+2):length(splt)])
matrix(vals, ncol=nrCols, byrow=TRUE, dimnames = list(NULL, cnames))
}else
txt
}
}
spill2txt <- function(mat, cpp = TRUE){
cols <- colnames(mat)
if(cpp)
{
spill_to_string(mat, cols)
}else
{
rNum <- as.character(nrow(mat))
clNames <- paste(cols,sep=",")
vec <- paste(c(t(mat)),sep=",",collapse=",")
paste(c(rNum,clNames,vec),sep=",",collapse=",")
}
}
## ==========================================================================
## create AnnotatedDataFrame describing the flow parameters (channels)
## - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
makeFCSparameters <- function(cn, txt, transformation, scale, decades,
realMin, id) {
dattype <- switch(readFCSgetPar(txt, "$DATATYPE"),
"I" = "integer",
"F" = "numeric",
"D" = "numeric",
stop(paste("Don't know how to deal with $DATATYPE",
readFCSgetPar(txt, "$DATATYPE"))))
npar <- length(cn)
if(missing(id)){
id = 1:npar
}
id <- paste("$P", id ,sep="")
range <- sapply(id, function(this_id){
rid <- paste("flowCore_", this_id,"Rmax",sep="")
original <- is.na(txt[rid])
if(!original)
as.numeric(txt[rid]) + 1
else
suppressWarnings(as.numeric(txt[paste(this_id,"R",sep="")]))
})
origRange <- range
range <- rbind(realMin,range-1)
## make sure the ranges are transformed along with the data
if(transformation & !scale){
ampliPar <- txt[paste(id,"E",sep="")]
noPnE <- is.na(ampliPar)
if(any(noPnE))
ampliPar[noPnE] <- "0,0"
ampli <- do.call(rbind,lapply(ampliPar, function(x)
as.numeric(unlist(strsplit(x,",")))))
for (i in 1:npar)
if(ampli[i,1] > 0 && dattype == "integer")
{
if(ampli[i,2] == 0)
ampli[i,2] = 1 #correct f2 value for legacy FCS
range[,i] <- 10^(range[,i]/(origRange[i]-1)*ampli[i,1])*ampli[i,2]
}
}
else if(scale)
range[2,] <- rep(10^decades, npar)
desc <- txt[paste(id,"S",sep="")]
desc <- gsub("^\\s+|\\s+$", "", desc)#trim the leading and tailing whitespaces
# replace the empty desc with NA
desc <- sapply(desc, function(thisDesc){
if(!nzchar(thisDesc))
NA
else
thisDesc
})
suppressWarnings(new("AnnotatedDataFrame",
data=data.frame(row.names=I(id),name=I(cn),
desc=I(desc),
range=as.numeric(txt[paste(id,"R",sep="")]), minRange=range[1,], maxRange=range[2,]),
varMetadata=data.frame(row.names=I(c("name","desc","range",
"minRange", "maxRange")),
labelDescription=I(c("Name of Parameter","Description of Parameter",
"Range of Parameter", "Minimum Parameter Value after Transforamtion",
"Maximum Parameter Value after Transformation")))))
}
## ==========================================================================
## match FCS parameters
## - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
readFCSgetPar <- function(x, pnam, strict=TRUE)
{
stopifnot(is.character(x), is.character(pnam))
i <- match(pnam, names(x))
if(any(is.na(i)) && strict)
stop(paste("Parameter(s)", pnam[is.na(i)], "not contained in 'x'\n"))
if(!strict)
{
if(!all(is.na(i)))
i[!is.na(i)] <- x[i[!is.na(i)]]
names(i) <- pnam
return(i)
}
return(x[i])
}
## ==========================================================================
## Find all data sections in a file and record their offsets.
## - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
findOffsets <- function(con,emptyValue=TRUE, dataset = NULL, ...)
{
offsets <- readFCSheader(con)
offsets <- matrix(offsets, nrow = 1, dimnames = list(NULL, names(offsets)))
txt <- readFCStext(con, offsets[1, ],emptyValue=emptyValue, ...)
addOff <- 0
if("$NEXTDATA" %in% names(txt)){
nd <- as.numeric(txt[["$NEXTDATA"]])
}else
nd <- 0
txt.list <- list(txt)
i <- 1
while(nd != 0)
{
i <- i + 1
addOff <- addOff + nd
offsets <- rbind(offsets, readFCSheader(con, addOff))
this.txt <- readFCStext(con, offsets[nrow(offsets),],emptyValue=emptyValue, ...)
nd <- as.numeric(this.txt[["$NEXTDATA"]])
txt.list[[i]] <- this.txt
}
## check for multiple data sets
nDataset <- length(txt.list)
if(nDataset == 1)
dataset <- 1
else
{
if(is.null(dataset))
{
warning(sprintf("The file contains %d additional data segment%s.\n",
nDataset-1, ifelse(nDataset>2, "s", "")),
"The default is to read the first segment only.\nPlease consider ",
"setting the 'dataset' argument.", call.=FALSE)
dataset <- 1
}
}
if(!is.numeric(dataset) || !dataset %in% seq_len(nDataset))
stop(sprintf("Argument 'dataset' must be an integer value in [1,%d].",
nDataset))
offsets <- offsets[dataset,]
txt <- txt.list[[dataset]]
# browser()
offsets <- checkOffset(offsets, txt, ...)
return(offsets)
}
#' Fix the offset when its values recorded in header and TEXT don't agree
#' @param offsets the named vector returned by \code{findOffsets}
#' @param x the text segmented returned by \code{readFCStext}
#' @param ignore.text.offset whether to ignore the offset info stored in TEXT segment
#' @param ... not used.
#' @return the updated offsets
checkOffset <- function(offsets, x, ignore.text.offset = FALSE, ...){
##for DATA segment exceeding 99,999,999 byte.
if(offsets["FCSversion"] >= 3){
realOff <- offsets - offsets[8]
# Let's not be too strick here as unfortunatelly, some files exported from FlowJo
# are missing the $BEGINDATA and $ENDDATA keywords and we still need to read those
datastart <- as.numeric(readFCSgetPar(x, "$BEGINDATA", strict=FALSE))
if (is.na(datastart)) {
if (realOff["datastart"] != 0) {
datastart = realOff["datastart"]
warning("Missing the required $BEGINDATA keyword! Reading data based on information in the FCS HEADER only.", call.=FALSE)
} else {
stop("Don't know where the data segment begins, there was no $BEGINDATA keyword and the FCS HEADER does not say it either.")
}
}
dataend <- as.numeric(readFCSgetPar(x, "$ENDDATA", strict=FALSE))
if (is.na(dataend)) {
if (realOff["dataend"] != 0) {
dataend = realOff["dataend"]
warning("Missing the required $ENDDATA keyword! Reading data based on information in the FCS HEADER only.", call.=FALSE)
} else {
stop("Don't know where the data segment ends, there was no $ENDDATA keyword and the FCS HEADER does not say it either.")
}
}
# when both are present and they don't agree with each other
if(realOff["datastart"] != datastart && realOff["datastart"]== 0){ #use the TEXT when header is 0
offsets["datastart"] <- datastart+offsets[8]
}
if(realOff["datastart"] != datastart && realOff["datastart"]!= 0){#trust the header when it is non-zero
msg <- paste0("The HEADER and the TEXT segment define different starting point ("
, offsets["datastart"], ":", datastart
, ") to read the data.")
if(ignore.text.offset)
warning(msg, " The values in TEXT are ignored!")
else
stop(msg)
}
#both are present and they don't agree
if(realOff["dataend"] != dataend && (realOff["dataend"]== 0 || realOff["dataend"]== 99999999)) {#use TEXT when either header is 0 or TEXT is 99999999
offsets["dataend"] <- dataend+offsets[8]
}
if(realOff["dataend"] != dataend && realOff["dataend"]!= 0 && realOff["dataend"]!= 99999999) {#otherwise trust the header
msg <- paste0("The HEADER and the TEXT segment define different ending point ("
, offsets["dataend"], ":", dataend
, ") to read the data.")
if(ignore.text.offset)
warning(msg, " The values in TEXT are ignored!")
else
stop(msg)
}
}
offsets
}
## ==========================================================================
## parse FCS file header
## - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
readFCSheader <- function(con, start=0)
{
seek(con, start)
version <- readChar(con, 6)
if(!version %in% c("FCS2.0", "FCS3.0", "FCS3.1"))
stop("This does not seem to be a valid FCS2.0, FCS3.0 or FCS3.1 file")
version <- substring(version, 4, nchar(version))
tmp <- readChar(con, 4)
stopifnot(tmp==" ")
coffs <- character(6)
for(i in 1:length(coffs))
coffs[i] <- readChar(con=con, nchars=8)
ioffs <- c(as.double(version), as.integer(coffs), as.integer(start))
names(ioffs) <- c("FCSversion", "textstart", "textend", "datastart",
"dataend", "anastart", "anaend", "additional")
ioffs[2:7] <- ioffs[2:7]+ioffs[8]
if(any(is.na(ioffs[2:5]) | ioffs[2:5]==""))
stop("Missing header information to start parsing the binary ",
"section of the file")
return(ioffs)
}
## ==========================================================================
## parse FCS file text section
## - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
readFCStext <- function(con, offsets,emptyValue = TRUE, cpp = TRUE, ...)
{
seek(con, offsets["textstart"])
## Certain software (e.g. FlowJo 8 on OS X) likes to put characters into
## files that readChar can't read, yet readBin, rawToChar and iconv can
## handle just fine.
txt <- readBin(con,"raw", offsets["textend"]-offsets["textstart"]+1)
txt <- iconv(rawToChar(txt), "", "latin1", sub="byte")
txt <- trimws(txt, "right")
# browser()
if(offsets["FCSversion"]<=2)##
{
delimiter <- substr(txt, 1, 1)
sp <- strsplit(substr(txt, 2, nchar(txt)), split=delimiter,
fixed=TRUE)[[1]]
rv <- c(offsets["FCSversion"], sp[seq(2, length(sp), by=2)])
names(rv) <- gsub("^ *| *$", "", c("FCSversion", sp[seq(1, length(sp)-1, by=2)]))
}else
{
#only apply the patch parser to FCS3
if(cpp)
rv = fcsTextParse(txt,emptyValue=emptyValue)
else
rv = fcs_text_parse(txt,emptyValue=emptyValue)
if(!"FCSversion"%in%names(rv))
rv <- c(offsets["FCSversion"], rv)
names(rv) <- gsub("^ *| *$", "", names(rv))#trim the leading and trailing whitespaces
}
return(rv)
}
## ==========================================================================
## a patch to fix the parsing issue when delimiter exists in the keyword value
##,which is allowed only when it is followed by another delimiter immediately
## Note that it is only applies to FCS3.0 because empty value is not valid value.
##however,this does not conform to FCS2.0,so this patch only applies to FCS3.0
## - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
fcs_text_parse = function(str,emptyValue) {
# browser()
pairs = c()
div = substr(str, 1, 1)
if(nchar(div) != 1) {
return(c())
}
# regexes require double-escaping (*sigh*)
# if(div == "\\") {
# div = "\\\\"
# }
# if(div=="|")
div<-paste("\\",div,sep="")
i = 2
repeat {
remaining = substr(str, i, nchar(str))
if(nchar(gsub(" ","",remaining)) == 0) {##filter out white spaces before check the length
break
}
key_end_regex <- paste("([^",div,"]",div,")", sep="")
#############################################################################################
##1.when empty value is allowed, we assume there is no double delimiters in any values,
## otherwise,it would break the parser
##2.when empty value is not allowed, we safely parse the double delimiters as the valid values
#############################################################################################
if(emptyValue)
{
value_end_regex <- div
final_end_regex <- paste(div,"$", sep="")
}else
{
value_end_regex <- paste("([^",div,"]",div,"[^",div,"])", sep="")
final_end_regex <- paste("[^",div,"]",div,"$", sep="")
}
# browser()
# find key end
divider_index = regexpr(key_end_regex, remaining, perl=TRUE)
if(divider_index < 0) {
if(i==2)
stop("ERROR: No second divider found\n")
else
{
warning("keyword: ",remaining," is dropped because no value found!")
break
}
}
divider_index = divider_index + 1
value_search = substr(remaining, divider_index + 1, nchar(remaining))
# find value end
value_end_index = regexpr(value_end_regex, value_search, perl=TRUE)
if(emptyValue)
value_end_index<-value_end_index-1
if(value_end_index < 0) {
value_end_index = regexpr(final_end_regex, value_search, perl=TRUE)
if(value_end_index < 0) {
if(emptyValue)
stop("No end found\n There could be double delimiter existing in keyword value.\nPlease set argument 'emptyValue' as FALSE and try again!")
else
stop("No end found\n There could be empty keyword value.\nPlease set argument 'emptyValue' as TRUE and try again!")
# return(c())
# break
}
}
value_end_index = divider_index + value_end_index
key = substr(remaining, 1, divider_index - 1)
value = substr(remaining, divider_index + 1, value_end_index)
#replace double delimiters with single one in the final output
value = gsub(paste(div,div,sep=''), div, value)
# cat("key: ", key, "\n")
# cat("value: ", value, "\n")
# cat("-----------------------\n")
pairs = c(pairs, value)
names(pairs)[length(pairs)] = key
i = i + value_end_index + 1
}
return(pairs)
}
# deprecated by cpp version
sortBytes1 <- function(bytes, byte_order){
nBytes <- length(byte_order)
nTotal <- length(bytes)
nElement <- nTotal / nBytes
#relative byte order for the entire vector
byte_orders <- rep(byte_order + 1 , nElement)
#absolute byte order for the entire vector
byte_orders <- byte_orders + rep((seq_len(nElement)-1) * 4, each = nBytes)
#re-order
ind <- order(byte_orders)
bytes[ind]
}
# Read raw FCS data. This is a wrapper around .readFCSdataRaw that calls the
# function with at most .Machine$integer.max bytes each time.
.readFCSdataRawMultiple <- function(con, dattype, count, size, signed, endian,
splitInt = FALSE, byte_order) {
chunk_size <- floor(.Machine$integer.max / size)
num_chunks <- ceiling(count / chunk_size)
items <- c()
for (chunk in seq(num_chunks)) {
if (chunk == num_chunks) {
chunk_count <- count - chunk_size * floor(count / chunk_size)
} else {
chunk_count <- chunk_size
}
items <-
c(items, .readFCSdataRaw(con, dattype, chunk_count, size, signed, endian,
splitInt, byte_order))
}
items
}
##read odd bitwidth by reading raw and and operating on raw vector
.readFCSdataRaw <- function(con, dattype, count, size, signed, endian,
splitInt = FALSE, byte_order) {
nBytes <- count * size
if (splitInt && (size != 4 || dattype != "integer")) {
stop("'splitInt = TRUE' is only valid for uint32")
}
if (size %in% c(1, 2, 4, 8)) {
if (splitInt) {
# Reorder bytes for mixed endian.
if (endian == "mixed") {
byte_order <- as.integer(strsplit(byte_order, ",")[[1]]) - 1
if(length(byte_order) != size) {
stop("byte order not consistent with bidwidths")
}
bytes <- readBin(con = con, what = "raw", n = nBytes, size = 1)
newBytes <- sortBytes(bytes, byte_order)
con <- newBytes
endian <- "little"
}
# Read uint32 as two uint16. Coerce count again to make sure that it's
# within the integer limit.
splitted <- readBin(con = con, what = dattype, n = as.integer(count * 2),
size = size / 2, signed = FALSE, endian = endian)
uint2double(splitted, endian == "big")
} else {
readBin(con = con, what = dattype, n = count, size = size,
signed = signed, endian=endian)
}
} else {
# Read raw byte stream first.
oldBytes <- readBin(con = con, what = "raw", n = nBytes, size = 1)
# Convert to bit vector.
oldBits <- rawToBits(oldBytes)
# Convert the data element to the non-odd bitwidth.
oldBitWidth <- size * 8
newBitWidth <- 2 ^ ceiling(log(oldBitWidth, 2))
newBits <-
unlist(lapply(1:count, function(i) {
start <- (i - 1) * oldBitWidth + 1
# Padding zeros.
c(oldBits[start:(start + oldBitWidth - 1)],
raw(newBitWidth-oldBitWidth))
}))
# Convert raw byte to corresponding type by readBin. packBits is
# least-significant bit first, so we need to make sure endian is set to
# "little" instead of the endian used in original FCS.
readBin(packBits(newBits, "raw"), what = dattype, n = count,
size = newBitWidth / 8, signed = signed, endian = "little")
}
}
check_channel_alias <- function(channel_alias){
if(is.null(channel_alias))
return (new.env(parent = emptyenv()))
else if(is(channel_alias, "data.frame"))
{
if(!setequal(c("alias", "channels"), colnames(channel_alias)))
stop("channel_alias must contain only 'alias' and 'channels' columns")
env <- new.env(parent = emptyenv())
apply(channel_alias, 1, function(row){
channels <- strsplit(split = ",", row["channels"])[[1]]
for(c in channels)
{
c <- trimws(c)
if(is.null(env[[c]]))
env[[c]] <- trimws(row[["alias"]])
else
stop("multiple entries found in channel_alias for: ", c)
}
})
return (env)
}else if(is(channel_alias, "environment"))
return (channel_alias)
else
stop("channel_alias must be either an environment or a data.frame")
}
update_channel_by_alias <- function(orig_chnl_names, channel_alias, silent = FALSE)
{
keys <- ls(channel_alias)
new_channels <- unlist(lapply(orig_chnl_names, function(col){
alias <- channel_alias[[col]]
if(is.null(alias))
{
#try partial match with case insensitive maching
#escape special characters by enclosing it with \Q and \E
ind <- unlist(lapply(keys, function(key){grepl(paste0("\\Q", key, "\\E"), col, ignore.case = TRUE)}))
if(sum(ind)>1)
stop(col, " is matched to the multiple entries in the channel_alias: ", paste(keys[ind], " "), "\n Try to modify channel_alias so that channel names are more specific! ")
else if(sum(ind) == 0)
return (col)
else
return (channel_alias[[keys[ind]]])
}else
return (alias)
}))
#validity check
tb <- table(new_channels)
is.dup <- tb > 1
if(any(is.dup))
{
dup <- names(tb)[is.dup]
dup.ind <- which(new_channels %in% dup)
for(chnl in dup){
chnl.ind <- which(new_channels == chnl)
new_channels[chnl.ind] <- paste0(chnl, "-", seq(tb[chnl]))
}
dt <- data.frame(orig_channel_name = orig_chnl_names[dup.ind], new_channel_name = new_channels[dup.ind])
if(!silent){
print(dt)
warning(paste0("\nchannel_alias: Multiple channels from one FCS are matched to the same alias!\n",
"Integer suffixes added to disambiguate channels.\n",
"It is also recommended to verify correct mapping of spillover matrix columns.\n"))
}
}
return (new_channels)
}
## ==========================================================================