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#' ---
#' title: Utilities shared between R code
#' author: G.J.J. van den Burg
#' date: 2019-09-29
#' license: See the LICENSE file.
#' copyright: 2019, The Alan Turing Institute
#' ---
library(RJSONIO)
printf <- function(...) invisible(cat(sprintf(...)));
load.dataset <- function(filename)
{
data <- fromJSON(filename)
# reformat the data to a data frame with a time index and the data values
tidx <- data$time$index
exp <- 0:(data$n_obs - 1)
if (all(tidx == exp) && length(tidx) == length(exp)) {
tidx <- NULL
} else {
tidx <- data$time$index
}
mat <- NULL
for (j in 1:data$n_dim) {
s <- data$series[[j]]
v <- NULL
for (i in 1:data$n_obs) {
val <- s$raw[[i]]
if (is.null(val)) {
v <- c(v, NA)
} else {
v <- c(v, val)
}
}
mat <- cbind(mat, v)
}
# We normalize to avoid issues with numerical precision.
mat <- scale(mat)
out <- list(original=data,
time=tidx,
mat=mat)
return(out)
}
prepare.result <- function(data, data.filename, status, error,
params, locations, runtime) {
out <- list(error=NULL)
cmd.args <- commandArgs(trailingOnly=F)
# the full command used
out$command <- paste(cmd.args, collapse=' ')
# get the name of the current script
file.arg <- "--file="
out$script <- sub(file.arg, "", cmd.args[grep(file.arg, cmd.args)])
# hash of the script
script.hash <- tools::md5sum(out$script)
names(script.hash) <- NULL
out$script_md5 <- script.hash
# hostname of the machine
hostname <- Sys.info()['nodename']
names(hostname) <- NULL
out$hostname <- hostname
# dataset name
out$dataset <- data$name
# dataset hash
data.hash <- tools::md5sum(data.filename)
names(data.hash) <- NULL
out$dataset_md5 <- data.hash
# status of running the script
out$status <- status
# error (if any)
if (!is.null(error))
out$error <- error
# parameters used
out$parameters <- params
# result
out$result <- list(cplocations=locations, runtime=runtime)
return(out)
}
make.param.list <- function(args, defaults)
{
params <- defaults
args.copy <- args
args.copy['input'] <- NULL
args.copy['output'] <- NULL
params <- modifyList(params, args.copy)
return(params)
}
dump.output <- function(out, filename) {
json.out <- toJSON(out, pretty=T)
if (!is.null(filename))
write(json.out, filename)
else
cat(json.out, '\n')
}
exit.error.multidim <- function(data, args, params) {
status = 'SKIP'
error = 'This method has no support for multidimensional data.'
out <- prepare.result(data, args$input, status, error, params, NULL, NA)
dump.output(out, args$output)
quit(save='no')
}
exit.with.error <- function(data, args, params, error) {
status = 'FAIL'
out <- prepare.result(data, args$input, status, error, params, NULL, NULL)
dump.output(out, args$output)
quit(save='no')
}
exit.success <- function(data, args, params, locations, runtime) {
status = 'SUCCESS'
error = NULL
out <- prepare.result(data, args$input, status, error, params, locations,
runtime)
dump.output(out, args$output)
}
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