library(parallel)
lorunwithout<-function (fit, year = NULL, fleet = NULL, map = fit$obj$env$map, ...) 
{
  data <- reduce(fit$data, year = year, fleet = fleet, conf = fit$conf)
  conf <- attr(data, "conf")
  fakefile <- file()
  sink(fakefile)
  saveConf(conf, file = "")
  sink()
  conf <- loadConf(data, fakefile, patch = TRUE)
  close(fakefile)
  par <- defpar(data, conf)
  par[!names(par) %in% c("logN", "logF", "logSW", "logCW", "logitMO", "logNM", "logFpar", "logSdLogObs", "transfIRARdist")] <-
      fit$pl[!names(fit$pl) %in% c("missing", "logN", "logF", "logSW", "logCW", "logitMO", "logNM", "logFpar", "logSdLogObs", "transfIRARdist")]
  ret <- sam.fit(data, conf, par, rm.unidentified = TRUE, map = map, 
      lower = fit$low, upper = fit$hig, ...)
  return(ret)
}
fixleaveout<-function (fit, fleet = as.list(2:fit$data$noFleets), ncores = detectCores(), ...) 
{
  if (ncores > 1) {
    cl <- makeCluster(ncores)
    on.exit(stopCluster(cl))
    clusterExport(cl, varlist = c("fit", "lorunwithout"), envir = environment())
    lib.ver <- dirname(path.package("stockassessment"))
    clusterExport(cl, varlist = "lib.ver", envir = environment())
    clusterEvalQ(cl, {library(stockassessment, lib.loc = lib.ver)})
    runs <- parLapply(cl, fleet, function(f) lorunwithout(fit, fleet = f, ...))
  }
  else {
    runs <- lapply(fleet, function(f) lorunwithout(fit, fleet = f, ...))
  }
  converg <- unlist(lapply(runs, function(x) x$opt$conv))
  if (any(converg != 0))warning(paste0("leavout run(s) ", paste0(which(converg != 0), collapse = ","), " did not converge."))
  names(runs) <- paste0("w.o. ", lapply(fleet, function(x) paste(attr(fit$data, "fleetNames")[x], collapse = " and ")))
  attr(runs, "fit") <- fit
  class(runs) <- "samset"
  runs
}