Run aquatic model ensemble

Run aquatic model ensemble

Usage

run_aeme(
  aeme,
  model,
  return_type = c("aeme", "exec_result", "both", "none"),
  ens_n = 1,
  model_controls = NULL,
  verbose = FALSE,
  debug = FALSE,
  timeout = Inf,
  parallel = FALSE,
  ncores,
  check_output = FALSE,
  path = "."
)

Arguments

aeme

aeme; object.

model

vector; of models to be used. Can be `dy_cd`, `glm_aed`, `gotm_wet`.

ens_n

numeric; ensemble number to allocate to model output which is loaded. Defaults to 1.

model_controls

dataframe; of configuration loaded from "model_controls.csv".

verbose

logical; print model output to console. Defaults to FALSE.

debug

logical; write debug log (Only DYRESM). Defaults to FALSE.

timeout

Timeout for the process, in seconds, or as a difftime object. If it is not finished before this, it will be killed.

parallel

logical; run models in parallel. Defaults to FALSE.

ncores

integer; number of cores to use for parallelization. Defaults to `min(c(detectCores() - 1, length(model)))`.

check_output

logical; check model output after running? Defaults to FALSE.

path

filepath; where input files are located relative to the current working directory.

return

logical; return model output within an `aeme` object? Defaults to TRUE.

Value

an `aeme` object with model output loaded.

Examples

aeme_file <- system.file("extdata/aeme.rds", package = "AEME")
aeme <- readRDS(aeme_file)
path <- tempdir()
model_controls <- get_model_controls()
model <- c("glm_aed")
aeme <- build_aeme(path = path, aeme = aeme, model = model,
model_controls = model_controls, ext_elev = 5)
#> ℹ Using observed water level
#> ℹ No missing values in observed water level. Using observed water level
#> ℹ Correcting water balance using estimated outflows (method = 2).
#> ℹ Calculating lake level using lake depth and a sinisoidal function.
#> ℹ Building GLM-AED2 for lake wainamu
#> ✔ GLM nml validation completed - no issues detected.
aeme <- run_aeme(aeme = aeme, model = model, path = path)
#> ℹ Running models... (Have you tried parallelizing?) [2026-02-05 00:00:13]
#> → GLM-AED running... [2026-02-05 00:00:13]
#> ✔ GLM-AED run successful! [2026-02-05 00:00:13]
#> ✔ Model run complete! [2026-02-05 00:00:13]
plot_output(aeme, model = model)
#> Warning: Removed 84 rows containing missing values or values outside the scale range
#> (`geom_col()`).