suppressPackageStartupMessages(library("optparse"))
# Make option list
option_list <- list(
make_option(c("-i", "--input"), type="character", default=NULL, help="Subject distances (use the *.desc extension) (required)", metavar="file"),
make_option(c("-v", "--voxels"), type="character", default=NULL, help="Range of voxels (columns) to extract. For example, '1' or '1:10' so basically it can be any R expression. Need this or -m/--mask", metavar="number"),
make_option(c("-m", "--mask"), type="character", default=NULL, help="Mask indicating voxels (columns) to extract with value of 2 and other voxels used for subject distances with value 1. Need this or -v/--voxels", metavar="file"),
make_option(c("-c", "--forks"), type="integer", default=1, help="Number of computer processors to use in parallel by forking the complete processing stream [default: %default]", metavar="number"),
make_option(c("-t", "--threads"), type="integer", default=1, help="Number of computer processors to use in parallel by multi-threading matrix algebra operations [default: %default]", metavar="number"),
make_option("--blocksize", type="integer", default=0, dest="blocksize", help="How many sets of columns or voxels should used in each iteration of computing the element-wise average (0 = auto) [default: %default]", metavar="number"),
make_option("--memlimit", type="double", default=4, dest="memlimit", help="If blocksize is set to auto (--blocksize=0), then will set the blocksize to use a maximum of RAM specified by this option [default: %default]", metavar="number"),
make_option("--overwrite", action="store_true", default=FALSE, help="Overwrite output if it already exists (default is not to overwrite already existing output)"),
make_option("--debug", action="store_true", default=FALSE, help="Like verbose but will also print more helpful error messages when --forks is >1"),
make_option("--verbose", action="store_true", default=TRUE, help="Print extra output [default]"),
make_option("--quiet", action="store_false", dest="verbose", help="Print little output")
)
# Make class/usage
parser <- OptionParser(usage = "%prog [options] outprefix (extension should not exist for outprefix)",
option_list=option_list,
add_help_option=TRUE)
# Parse
parser_out <- parse_args(parser, positional_arguments = TRUE)
args <- parser_out$args
opts <- parser_out$options
# Check options/arguments
if (length(args) != 1) {
print_help(parser)
quit(save="no", status=1)
}
saved_opts <- list(args=args, opts=opts)
tryCatch({
# load connectir
suppressWarnings(suppressPackageStartupMessages(library("connectir")))
# parallel processing setup
set_parallel_procs(opts$forks, opts$threads, opts$verbose)
# use foreach parallelization and shared memory?
parallel_forks <- ifelse(opts$forks == 1, FALSE, TRUE)
###
# Check Inputs
###
vcat(opts$verbose, "Checking options")
# check variables
if (is.null(opts$input))
stop("must specify -i/--input")
if (opts$overwrite)
stop("Right now the overwrite function isn't implemented")
if (is.null(opts$voxels) && is.null(opts$mask))
stop("Must specify either -v/--voxels or -m/--mask")
if (!is.null(opts$voxels) && !is.null(opts$mask))
stop("Must specify either -v/--voxels or -m/--mask (not both)")
###
# Setup inputs
###
vcat(opts$verbose, "Setting/checking inputs")
# check/set input
opts$input <- abspath(opts$input)
if (!file.exists(opts$input))
vstop("-i/--input '%s' does not exist", opts$input)
# check/set output
outprefix <- abspath(args[1])
if (!file.exists(dirname(args[1]))) {
vcat(opts$verbose, "Output directory '%s' does not exist, creating",
dirname(args[1]))
dir.create(dirname(args[1]))
}
if (opts$debug) {
verbosity <- 2
} else if (opts$verbose) {
verbosity <- 1
} else {
verbosity <- 0
}
###
# Read inputs
###
vcat(opts$verbose, "Reading in input")
imat <- attach.big.matrix(opts$input)
if (!is.null(opts$mask)) {
mask <- read.nifti.image(opts$mask)
# check that mask only has needed values
if (!all(sort(unique(mask)) != c(0,1,2))) {
vstop("Mask should only have 0,1,2 as it's unique values. Something else was found")
}
# check that mask is same size as imat
if (sum(mask>0) != ncol(imat)) {
vstop("mask should have the same number of non-zero values as columns in the subject distances")
}
voxs <- which(mask==2)
} else if (!is.null(opts$voxels)) {
voxs <- eval(parse(text=opts$voxels))
}
###
# Setup outputs
###
vcat(opts$verbose, "Setup outputs")
omat <- big.matrix(nrow(imat), length(voxs), type=typeof(imat), init=0,
backingfile=paste(basename(outprefix), ".bin", sep=""),
descriptorfile=paste(basename(outprefix), ".desc", sep=""),
backingpath=dirname(outprefix))
###
# Subset / Save
###
vcat(opts$verbose, "Getting subset of voxels")
deepcopy(x=imat, cols=voxs, y=omat)
}, warning = function(ex) {
cat("\nA warning was detected: \n")
cat(ex$message, "\n\n")
cat("Called by: \n")
print(ex$call)
cat("\nSaving options...\n")
save(saved_opts, file="called_options.rda")
}, error = function(ex) {
cat("\nAn error was detected: \n")
cat(ex$message, "\n\n")
cat("Called by: \n")
print(ex$call)
cat("\nSaving options...\n")
save(saved_opts, file="called_options.rda")
}, interrupt = function(ex) {
cat("\nSaving options...\n")
save(saved_opts, file="called_options.rda")
cat("\nKill signal sent. Trying to clean up...\n")
rm(list=ls())
gc(FALSE)
cat("...success\n")
}, finally = {
cat("\nRemoving everything from memory\n")
rm(list=ls())
gc(FALSE)
cat("...sucesss\n")
})
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