R/LSSS2TSD.R
In arnejohannesholmin/sonR: Library for reading, processing and converting sonar data to the TSD format
Defines functions
LSSS2TSD
Documented in
LSSS2TSD
#*********************************************
#*********************************************
#' Convert from LSSS Profos files to TSD files.
#'
#' \code{LSSS2TSD} Converts from LSSS Profos export files to TSD files, readable by R using the functions read.TSD, read.TSDs and read.event.
#'
# See EKRaw2TSD for parameter descriptions.
#'
#' @return
#'
#' @examples
#' \dontrun{}
#'
#' @importFrom data.table rbindlist
#' @importFrom SimradRaw soundbeam_range
#' @importFrom TSD arr.ind2ind write.TSD NAs zeros utim2ftim combine.TSD papply
#' @importFrom utils tail head read.table
#'
#' @export
#' @rdname EKRaw2TSD
#'
LSSS2TSD <- function(event=NULL, filesize=3e8, chunksize=1e8, keep.temp=FALSE, cores=1, ...){
############### LOG: ###############
# Start: 2016-12-06 - Clean version.
##################################################
##################################################
########## Preparation ##########
### Functions: ###
# Get the string between two other strings:
getStringBetween <- function(x, s1, s2){
gsub(paste0(".*", s1, "\\s*|", s2, ".*"), "", x)
}
# Get the esnm from a string:
getESNM <- function(x){
toupper(getStringBetween(x, s1="Ping_", s2="-D"))
}
# Read sample data using read.table:
readSampleData <- function(x){
# Get sample data:
read.table(x, header=TRUE, sep=",")
}
# Get the radial resolutions of a school file:
readRange <- function(x){
# Get sample data:
read.table(x, header=TRUE, sep=",")$Range
}
# Get school ID with file identifiers as names:
getSchoolID <- function(l, n=10){
getSchoolIDOne <- function(x, n){
l <- readLines(x, n=n)
hash <- startsWith(l, "#")
# Get school ID:
schoolIDString <- "# School id: "
schoolIDLine <- l[startsWith(l, schoolIDString)]
as.numeric(substring(schoolIDLine, nchar(schoolIDString)+1))
}
getFileIDOne <- function(x, n){
l <- readLines(x, n=n)
hash <- startsWith(l, "#")
# Get school ID:
fileIDString <- "# Ping: "
fileIDLine <- l[startsWith(l, fileIDString)]
substring(fileIDLine, nchar(fileIDString)+1)
}
schoolID <- unlist(lapply(l, getSchoolIDOne, n=n))
fileID <- unlist(lapply(l, getFileIDOne, n=n))
names(schoolID) <- fileID
schoolID
}
# Converts full data to segmentation data:
#getSeg <- function(xx){
# present <- which(!is.na(xx))
# cbind(present, xx[present])
#}
# Reads acoustic data, range indices and beam indices:
getSeg <- function(file, beams){
x <- read.table(file, header=TRUE, sep=",")
#out <- NAs(max(beams$lenb), beams$numb[1])
ranges <- soundbeam_range(beams)
edges <- soundbeam_range(beams, pos="edge")
rangeInd <- findInterval(x$Range, edges)
beamsInd <- colnames(x)
beamsInd <- beamsInd[startsWith(beamsInd, "Beam")]
beamsInd <- as.numeric(substring(beamsInd, 5)) + 1
#out[rangeInd, beamsInd] <- as.matrix(x[,-1])
ind <- arr.ind2ind(as.matrix(expand.grid(rangeInd, beamsInd)), c(max(beams$lenb), beams$numb[1]))
data <- x[,-1]
noNA <- !is.na(data)
list(ind=ind[noNA], data=data[noNA])
}
# Read all the files for one ping, merge the schools, and write the pingsfile:
getOnePing <- function(pingInd, files, outfiles, vessel, beams){
# Read the segmentation masks:
temp <- lapply(files[[pingInd]], getSeg, beams=beams)
# Combine all matrices of indices and data:
temp <- data.table::rbindlist(temp)
# Sum over all indices (allowing for several overlapping schools, which is unlikely, but still the method is simple):
temp <- tapply(temp[[2]], temp[[1]], sum)
# Save compressed data (indices and segmented data):
pings <- list()
pings$vbsc = 10^(temp/10)
pings$vxIX = as.numeric(names(temp))
## Merge the data, counting NAs as 0:
#out <- NAs(max(beams$lenb), beams$numb[1])
#out[as.numeric(names(temp))] <- temp
pings$utim <- vessel$utim[pingInd]
#pings$vbsc <- 10^(out/10)
pings$lenb <- beams$lenb[,pingInd]
pings$numb <- beams$numb[pingInd]
# Write the data to individual pings files and merge later:
write.TSD(pings, con=outfiles[pingInd], numt=1)
}
### End of functions: ###
# Default beams values:
defaultBeams <- list(numb=NULL, lenb=NULL, psze=-7, diraSpan=c(0, 360), asps=1480, bwtx=NA, bwty=NA, eqba=NA, freq=NA, sacr=NA, tpow=NA, gai1=NA, gai2=NA, bmmd=NA)
if(length(event)==0){
return(defaultBeams)
}
ll <- list(...)
beamsNames <- intersect(names(defaultBeams), names(ll))
if(length(beamsNames)){
defaultBeams[beamsNames] <- ll[beamsNames]
}
# Extract the defaults:
numb <- defaultBeams$numb
lenb <- defaultBeams$lenb
psze <- defaultBeams$psze
diraSpan <- defaultBeams$diraSpan
if(any(diraSpan > 2*pi)){
diraSpan <- diraSpan * pi/180
}
asps <- defaultBeams$asps
bwtx <- defaultBeams$bwtx
bwty <- defaultBeams$bwty
eqba <- defaultBeams$eqba
freq <- defaultBeams$freq
sacr <- defaultBeams$sacr
tpow <- defaultBeams$tpow
gai1 <- defaultBeams$gai1
gai2 <- defaultBeams$gai2
bmmd <- defaultBeams$bmmd
# Get the list of files, slit into the sub directories:
dirs = list.dirs(event)
l = list.files(event, recursive=TRUE, full.names=TRUE)
lclean <- gsub(paste0(event, "/"), "", l, fixed=TRUE)
lclean <- split(lclean, dirname(lclean))
# Add the event again:
lclean <- lapply(lclean, function(xx) file.path(event, xx))
if(any(sapply(lclean[c("Export/ProfosSchoolSamples", "Reports/profos")], length)==0)){
warning("The event must contain the directories \"Export/ProfosSchoolSamples\" and \"Reports/profos\"")
}
# Get the type of sonar:
eventname = basename(event)
esnm <- getESNM(head(lclean[["Export/ProfosSchoolSamples"]], 1))
# Create the TSD directory and define file names:
tsdDir <- file.path(event, esnm, "tsd")
tsdDirIndividualPings <- file.path(event, esnm, "tsd_individual")
suppressWarnings(dir.create(tsdDir, recursive=TRUE))
suppressWarnings(dir.create(tsdDirIndividualPings, recursive=TRUE))
vesselfile <- file.path(tsdDir, paste0(eventname, ".vessel"))
beamsfile <- file.path(tsdDir, paste0(eventname, ".beams"))
########### Processing: ###########
# Define list storing the data:
beams <- list()
vessel <- list()
pings <- list()
# Read the compressed school data containing vessel information. This is the files ending with pp.txt (denoting "per ping"):
ppFile <- lclean[["Reports/profos"]]
ppFile <- ppFile[substring(ppFile, nchar(ppFile)-5)=="pp.txt"]
ppData <- read.table(ppFile, header=TRUE)
# Get school IDs:
schoolID <- ppData$Id
# Get the school IDs in the sample data files:
schoolIDFiles <- getSchoolID(lclean[["Export/ProfosSchoolSamples"]])
# Order the school files by the order in the ppFile:
lclean[["Export/ProfosSchoolSamples"]] <- lclean[["Export/ProfosSchoolSamples"]][match(as.character(ppData$File), names(schoolIDFiles))]
##### Vessel data: #####
# 1. Get the time:
vessel$utim <- unclass(as.POSIXct(paste(ppData$Date, ppData$Time), tz="UTC"))
# The vessel times can be duplicated if there are more than one school in one or more pings:
numt <- length(vessel$utim)
# 2. Get the vessel position:
vessel$lonv <- ppData$Ship.lon
vessel$latv <- ppData$Ship.lat
# 3. Get the vessel speed:
vessel$ispv <- ppData$Ship.speed
# 4. Get the vessel pitch (rtxv), roll (rtyv), heading (rtzv):
vessel$rtxv <- NAs(numt)
vessel$rtyv <- NAs(numt)
vessel$rtzv <- (-ppData$Ship.heading * pi / 180) %% (2*pi)
# 5. Get the vessel heave:
vessel$pszv <- NAs(numt)
# 6. Get the time offset of the vessel information:
vessel$terr <- zeros(numt)
# Sort the vessel information by the time steps:
vessel <- lapply(vessel, function(xx) xx[order(vessel$utim)])
# Group the school files into time steps:
lclean[["Export/ProfosSchoolSamples"]] <- split(lclean[["Export/ProfosSchoolSamples"]], sort(unique(vessel$utim)))
pingInd <- seq_along(lclean[["Export/ProfosSchoolSamples"]])
# Uniquify the vesse data:
duputim <- duplicated(vessel$utim)
vessel <- lapply(vessel, "[", !duputim)
##### Beams data: #####
# 1. Get the sonar name:
beams$esnm <- rep(esnm, numt)
# 2. Get the UNIX time:
beams$utim <- vessel$utim
beams$asps <- rep(asps, numt)
# Get number of beams:
if(length(lenb)==0){
if(esnm=="SN90"){
numb <- 256
}
else if(esnm %in% c("SU90", "SX90", "SH90", "SX80", "SH80")){
numb <- 64
}
}
beams$numb <- rep(numb, numt)
if(length(freq)==1 && is.na(freq)){
warning("freq must be set manually")
}
beams$freq <- matrix(freq, nrow=numb, ncol=numt)
beams$absr <- NAs(numb, numt)
# Read the ranges of all files, and get the radial resolution as exactly as possible:
dd <- papply(lclean[["Export/ProfosSchoolSamples"]], readRange, cores=cores, outfile=FALSE)
beams$rres <- rep(mean(unlist(lapply(dd, diff))), numt)
maxRange <- max(unlist(lapply(dd, max)))
if(length(lenb)==0){
lenb <- ceiling(maxRange / beams$rres[1])
}
beams$lenb <- matrix(lenb, nrow=numb, ncol=numt)
# Get also the data from the first file of school data:
beams$sint <- rep(round(2 * beams$rres[1] / asps * 1e6) * 1e-6, numt)
# Update asps:
beams$asps <- rep(2 * beams$rres[1] / beams$sint[1], numt)
beams$plsl <- NAs(numt)
beams$psze <- NAs(numt)
if(length(lenb)==1 && is.na(lenb)){
warning("lenb must be set manually")
}
# Create a sequence from diraSpan (if given as 0 to 2*pi, assume this is from beam 1 to beam 1):
full <- identical(range(diraSpan), c(0,2*pi))
deltadira <- diff(diraSpan) / (beams$numb[1] + if(full) 1 else 0)
beams$dira <- matrix(seq(diraSpan[1], by=deltadira, l=numb), nrow=numb, ncol=numt)
# Add 90 degrees and convert to radians
beams$dire <- matrix((-ppData$Trans.tilt + 90) * pi/180, nrow=numb, ncol=numt, byrow=TRUE)
# 1. Get the time:
if((length(bwtx)==1 && is.na(bwtx)) || (length(bwty)==1 && is.na(bwty))){
warning("bwtx and bwty must be set manually")
}
beams$bwtx <- zeros(numb, numt) + bwtx
beams$bwty <- zeros(numb, numt) + bwty
beams$eqba <- zeros(numb, numt) + eqba
beams$sacr <- zeros(numb, numt) + sacr
beams$tpow <- zeros(numb, numt) + tpow
beams$gai1 <- zeros(numb, numt) + gai1
beams$gai2 <- zeros(numb, numt) + gai2
beams$bmmd <- zeros(numt) + bmmd
# Write the vessel data:
write.TSD(vessel, con=vesselfile, numt=numt)
# Write the vessel data:
write.TSD(beams, con=beamsfile, numt=numt)
##### Pings: #####
# Get file names of the pings:
pingsfilesDateTime <- utim2ftim(as.numeric(unlist(names(lclean[["Export/ProfosSchoolSamples"]]))), "Dyyyymmdd-THHMMSS")
pingsfiles <- file.path(tsdDirIndividualPings, paste0(eventname, pingsfilesDateTime, ".pings"))
# Parallel converting of the school files:
papply(pingInd, getOnePing, files=lclean[["Export/ProfosSchoolSamples"]], outfiles=pingsfiles, vessel=vessel, beams=beams, cores=cores, outfile=FALSE)
# Simply merge the pings files (pad=FALSE ensures that segmented data, using the vxIX, are saved in a list, and not padded with NAs):
pingsfiles = combine.TSD(pingsfiles, dir=tsdDir, reserve=TRUE, filesize=filesize, chunksize=chunksize, cores=cores, pad=FALSE, ...)
# Delete the individual pings:
if(!keep.temp){
unlink(tsdDirIndividualPings, recursive=TRUE)
}
# Return individual lists or merge to one list:
invisible(list(vesselfile=vesselfile, beamsfile=beamsfile, pingsfiles=pingsfiles))
##################################################
##################################################
}
arnejohannesholmin/sonR documentation built on April 14, 2024, 11:39 p.m.
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Defines functions LSSS2TSD
Documented in LSSS2TSD
#*********************************************
#*********************************************
#' Convert from LSSS Profos files to TSD files.
#'
#' \code{LSSS2TSD} Converts from LSSS Profos export files to TSD files, readable by R using the functions read.TSD, read.TSDs and read.event.
#'
# See EKRaw2TSD for parameter descriptions.
#'
#' @return
#'
#' @examples
#' \dontrun{}
#'
#' @importFrom data.table rbindlist
#' @importFrom SimradRaw soundbeam_range
#' @importFrom TSD arr.ind2ind write.TSD NAs zeros utim2ftim combine.TSD papply
#' @importFrom utils tail head read.table
#'
#' @export
#' @rdname EKRaw2TSD
#'
LSSS2TSD <- function(event=NULL, filesize=3e8, chunksize=1e8, keep.temp=FALSE, cores=1, ...){
############### LOG: ###############
# Start: 2016-12-06 - Clean version.
##################################################
##################################################
########## Preparation ##########
### Functions: ###
# Get the string between two other strings:
getStringBetween <- function(x, s1, s2){
gsub(paste0(".*", s1, "\\s*|", s2, ".*"), "", x)
}
# Get the esnm from a string:
getESNM <- function(x){
toupper(getStringBetween(x, s1="Ping_", s2="-D"))
}
# Read sample data using read.table:
readSampleData <- function(x){
# Get sample data:
read.table(x, header=TRUE, sep=",")
}
# Get the radial resolutions of a school file:
readRange <- function(x){
# Get sample data:
read.table(x, header=TRUE, sep=",")$Range
}
# Get school ID with file identifiers as names:
getSchoolID <- function(l, n=10){
getSchoolIDOne <- function(x, n){
l <- readLines(x, n=n)
hash <- startsWith(l, "#")
# Get school ID:
schoolIDString <- "# School id: "
schoolIDLine <- l[startsWith(l, schoolIDString)]
as.numeric(substring(schoolIDLine, nchar(schoolIDString)+1))
}
getFileIDOne <- function(x, n){
l <- readLines(x, n=n)
hash <- startsWith(l, "#")
# Get school ID:
fileIDString <- "# Ping: "
fileIDLine <- l[startsWith(l, fileIDString)]
substring(fileIDLine, nchar(fileIDString)+1)
}
schoolID <- unlist(lapply(l, getSchoolIDOne, n=n))
fileID <- unlist(lapply(l, getFileIDOne, n=n))
names(schoolID) <- fileID
schoolID
}
# Converts full data to segmentation data:
#getSeg <- function(xx){
# present <- which(!is.na(xx))
# cbind(present, xx[present])
#}
# Reads acoustic data, range indices and beam indices:
getSeg <- function(file, beams){
x <- read.table(file, header=TRUE, sep=",")
#out <- NAs(max(beams$lenb), beams$numb[1])
ranges <- soundbeam_range(beams)
edges <- soundbeam_range(beams, pos="edge")
rangeInd <- findInterval(x$Range, edges)
beamsInd <- colnames(x)
beamsInd <- beamsInd[startsWith(beamsInd, "Beam")]
beamsInd <- as.numeric(substring(beamsInd, 5)) + 1
#out[rangeInd, beamsInd] <- as.matrix(x[,-1])
ind <- arr.ind2ind(as.matrix(expand.grid(rangeInd, beamsInd)), c(max(beams$lenb), beams$numb[1]))
data <- x[,-1]
noNA <- !is.na(data)
list(ind=ind[noNA], data=data[noNA])
}
# Read all the files for one ping, merge the schools, and write the pingsfile:
getOnePing <- function(pingInd, files, outfiles, vessel, beams){
# Read the segmentation masks:
temp <- lapply(files[[pingInd]], getSeg, beams=beams)
# Combine all matrices of indices and data:
temp <- data.table::rbindlist(temp)
# Sum over all indices (allowing for several overlapping schools, which is unlikely, but still the method is simple):
temp <- tapply(temp[[2]], temp[[1]], sum)
# Save compressed data (indices and segmented data):
pings <- list()
pings$vbsc = 10^(temp/10)
pings$vxIX = as.numeric(names(temp))
## Merge the data, counting NAs as 0:
#out <- NAs(max(beams$lenb), beams$numb[1])
#out[as.numeric(names(temp))] <- temp
pings$utim <- vessel$utim[pingInd]
#pings$vbsc <- 10^(out/10)
pings$lenb <- beams$lenb[,pingInd]
pings$numb <- beams$numb[pingInd]
# Write the data to individual pings files and merge later:
write.TSD(pings, con=outfiles[pingInd], numt=1)
}
### End of functions: ###
# Default beams values:
defaultBeams <- list(numb=NULL, lenb=NULL, psze=-7, diraSpan=c(0, 360), asps=1480, bwtx=NA, bwty=NA, eqba=NA, freq=NA, sacr=NA, tpow=NA, gai1=NA, gai2=NA, bmmd=NA)
if(length(event)==0){
return(defaultBeams)
}
ll <- list(...)
beamsNames <- intersect(names(defaultBeams), names(ll))
if(length(beamsNames)){
defaultBeams[beamsNames] <- ll[beamsNames]
}
# Extract the defaults:
numb <- defaultBeams$numb
lenb <- defaultBeams$lenb
psze <- defaultBeams$psze
diraSpan <- defaultBeams$diraSpan
if(any(diraSpan > 2*pi)){
diraSpan <- diraSpan * pi/180
}
asps <- defaultBeams$asps
bwtx <- defaultBeams$bwtx
bwty <- defaultBeams$bwty
eqba <- defaultBeams$eqba
freq <- defaultBeams$freq
sacr <- defaultBeams$sacr
tpow <- defaultBeams$tpow
gai1 <- defaultBeams$gai1
gai2 <- defaultBeams$gai2
bmmd <- defaultBeams$bmmd
# Get the list of files, slit into the sub directories:
dirs = list.dirs(event)
l = list.files(event, recursive=TRUE, full.names=TRUE)
lclean <- gsub(paste0(event, "/"), "", l, fixed=TRUE)
lclean <- split(lclean, dirname(lclean))
# Add the event again:
lclean <- lapply(lclean, function(xx) file.path(event, xx))
if(any(sapply(lclean[c("Export/ProfosSchoolSamples", "Reports/profos")], length)==0)){
warning("The event must contain the directories \"Export/ProfosSchoolSamples\" and \"Reports/profos\"")
}
# Get the type of sonar:
eventname = basename(event)
esnm <- getESNM(head(lclean[["Export/ProfosSchoolSamples"]], 1))
# Create the TSD directory and define file names:
tsdDir <- file.path(event, esnm, "tsd")
tsdDirIndividualPings <- file.path(event, esnm, "tsd_individual")
suppressWarnings(dir.create(tsdDir, recursive=TRUE))
suppressWarnings(dir.create(tsdDirIndividualPings, recursive=TRUE))
vesselfile <- file.path(tsdDir, paste0(eventname, ".vessel"))
beamsfile <- file.path(tsdDir, paste0(eventname, ".beams"))
########### Processing: ###########
# Define list storing the data:
beams <- list()
vessel <- list()
pings <- list()
# Read the compressed school data containing vessel information. This is the files ending with pp.txt (denoting "per ping"):
ppFile <- lclean[["Reports/profos"]]
ppFile <- ppFile[substring(ppFile, nchar(ppFile)-5)=="pp.txt"]
ppData <- read.table(ppFile, header=TRUE)
# Get school IDs:
schoolID <- ppData$Id
# Get the school IDs in the sample data files:
schoolIDFiles <- getSchoolID(lclean[["Export/ProfosSchoolSamples"]])
# Order the school files by the order in the ppFile:
lclean[["Export/ProfosSchoolSamples"]] <- lclean[["Export/ProfosSchoolSamples"]][match(as.character(ppData$File), names(schoolIDFiles))]
##### Vessel data: #####
# 1. Get the time:
vessel$utim <- unclass(as.POSIXct(paste(ppData$Date, ppData$Time), tz="UTC"))
# The vessel times can be duplicated if there are more than one school in one or more pings:
numt <- length(vessel$utim)
# 2. Get the vessel position:
vessel$lonv <- ppData$Ship.lon
vessel$latv <- ppData$Ship.lat
# 3. Get the vessel speed:
vessel$ispv <- ppData$Ship.speed
# 4. Get the vessel pitch (rtxv), roll (rtyv), heading (rtzv):
vessel$rtxv <- NAs(numt)
vessel$rtyv <- NAs(numt)
vessel$rtzv <- (-ppData$Ship.heading * pi / 180) %% (2*pi)
# 5. Get the vessel heave:
vessel$pszv <- NAs(numt)
# 6. Get the time offset of the vessel information:
vessel$terr <- zeros(numt)
# Sort the vessel information by the time steps:
vessel <- lapply(vessel, function(xx) xx[order(vessel$utim)])
# Group the school files into time steps:
lclean[["Export/ProfosSchoolSamples"]] <- split(lclean[["Export/ProfosSchoolSamples"]], sort(unique(vessel$utim)))
pingInd <- seq_along(lclean[["Export/ProfosSchoolSamples"]])
# Uniquify the vesse data:
duputim <- duplicated(vessel$utim)
vessel <- lapply(vessel, "[", !duputim)
##### Beams data: #####
# 1. Get the sonar name:
beams$esnm <- rep(esnm, numt)
# 2. Get the UNIX time:
beams$utim <- vessel$utim
beams$asps <- rep(asps, numt)
# Get number of beams:
if(length(lenb)==0){
if(esnm=="SN90"){
numb <- 256
}
else if(esnm %in% c("SU90", "SX90", "SH90", "SX80", "SH80")){
numb <- 64
}
}
beams$numb <- rep(numb, numt)
if(length(freq)==1 && is.na(freq)){
warning("freq must be set manually")
}
beams$freq <- matrix(freq, nrow=numb, ncol=numt)
beams$absr <- NAs(numb, numt)
# Read the ranges of all files, and get the radial resolution as exactly as possible:
dd <- papply(lclean[["Export/ProfosSchoolSamples"]], readRange, cores=cores, outfile=FALSE)
beams$rres <- rep(mean(unlist(lapply(dd, diff))), numt)
maxRange <- max(unlist(lapply(dd, max)))
if(length(lenb)==0){
lenb <- ceiling(maxRange / beams$rres[1])
}
beams$lenb <- matrix(lenb, nrow=numb, ncol=numt)
# Get also the data from the first file of school data:
beams$sint <- rep(round(2 * beams$rres[1] / asps * 1e6) * 1e-6, numt)
# Update asps:
beams$asps <- rep(2 * beams$rres[1] / beams$sint[1], numt)
beams$plsl <- NAs(numt)
beams$psze <- NAs(numt)
if(length(lenb)==1 && is.na(lenb)){
warning("lenb must be set manually")
}
# Create a sequence from diraSpan (if given as 0 to 2*pi, assume this is from beam 1 to beam 1):
full <- identical(range(diraSpan), c(0,2*pi))
deltadira <- diff(diraSpan) / (beams$numb[1] + if(full) 1 else 0)
beams$dira <- matrix(seq(diraSpan[1], by=deltadira, l=numb), nrow=numb, ncol=numt)
# Add 90 degrees and convert to radians
beams$dire <- matrix((-ppData$Trans.tilt + 90) * pi/180, nrow=numb, ncol=numt, byrow=TRUE)
# 1. Get the time:
if((length(bwtx)==1 && is.na(bwtx)) || (length(bwty)==1 && is.na(bwty))){
warning("bwtx and bwty must be set manually")
}
beams$bwtx <- zeros(numb, numt) + bwtx
beams$bwty <- zeros(numb, numt) + bwty
beams$eqba <- zeros(numb, numt) + eqba
beams$sacr <- zeros(numb, numt) + sacr
beams$tpow <- zeros(numb, numt) + tpow
beams$gai1 <- zeros(numb, numt) + gai1
beams$gai2 <- zeros(numb, numt) + gai2
beams$bmmd <- zeros(numt) + bmmd
# Write the vessel data:
write.TSD(vessel, con=vesselfile, numt=numt)
# Write the vessel data:
write.TSD(beams, con=beamsfile, numt=numt)
##### Pings: #####
# Get file names of the pings:
pingsfilesDateTime <- utim2ftim(as.numeric(unlist(names(lclean[["Export/ProfosSchoolSamples"]]))), "Dyyyymmdd-THHMMSS")
pingsfiles <- file.path(tsdDirIndividualPings, paste0(eventname, pingsfilesDateTime, ".pings"))
# Parallel converting of the school files:
papply(pingInd, getOnePing, files=lclean[["Export/ProfosSchoolSamples"]], outfiles=pingsfiles, vessel=vessel, beams=beams, cores=cores, outfile=FALSE)
# Simply merge the pings files (pad=FALSE ensures that segmented data, using the vxIX, are saved in a list, and not padded with NAs):
pingsfiles = combine.TSD(pingsfiles, dir=tsdDir, reserve=TRUE, filesize=filesize, chunksize=chunksize, cores=cores, pad=FALSE, ...)
# Delete the individual pings:
if(!keep.temp){
unlink(tsdDirIndividualPings, recursive=TRUE)
}
# Return individual lists or merge to one list:
invisible(list(vesselfile=vesselfile, beamsfile=beamsfile, pingsfiles=pingsfiles))
##################################################
##################################################
}
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