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diff --git a/execs/R/utils.R b/execs/R/utils.R
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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)
+}