## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(collapse = TRUE, comment = "#>", eval = FALSE)
library(flexstanr)

## -----------------------------------------------------------------------------
# stan_options(threading = TRUE)

## -----------------------------------------------------------------------------
# opts <- stan_options(chains = 4, threading = TRUE)
# #> flexstanr: threading enabled. Using 16 of 16 available cores: 4 chains in
# #> parallel, 4 threads per chain. Pass max_cores to leave some cores free.

## -----------------------------------------------------------------------------
# fit <- fit_model("my_model", dat_stan = dat, init = init, stan_opts = opts)

## -----------------------------------------------------------------------------
# # use at most 4 cores, however many the machine has
# stan_options(chains = 4, threading = TRUE, max_cores = 4)

## -----------------------------------------------------------------------------
# run_my_fit <- function(dat_stan, init, stan_opts = stan_options()) {
#   if (test_threaded(stan_opts) && !model_is_threaded) {
#     warning(
#       "threads were requested but this model does not use reduce_sum(); ",
#       "it will run one thread per chain. Run more chains, use the threaded ",
#       "model variant, or set threading = FALSE.",
#       call. = FALSE
#     )
#   }
#   fit_model("my_model", dat_stan = dat_stan, init = init, stan_opts = stan_opts)
# }

## -----------------------------------------------------------------------------
# options(mc.cores = 6)
# stan_options(chains = 4, threading = TRUE)   # sees at most 6 cores

## -----------------------------------------------------------------------------
# # fit.R -- no core arithmetic; availableCores() picks up SLURM_CPUS_PER_TASK = 8
# opts <- stan_options(chains = 4, iter = 2000, threading = TRUE)
# fit  <- fit_model("my_model", dat_stan = dat, init = init, stan_opts = opts)
# saveRDS(fit, "fit.rds")

## -----------------------------------------------------------------------------
# i    <- Sys.getenv("SLURM_ARRAY_TASK_ID")
# opts <- stan_options(chains = 1, seed = as.integer(i), threading = TRUE)
# fit  <- fit_model("my_model", dat_stan = dat, init = init, stan_opts = opts)
# saveRDS(fit, sprintf("chain-%s.rds", i))