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Run sensitivity analysis on AEME model parameters

Source: R/sa_aeme.R
sa_aeme.Rd

calib_model() runs the model and compares it against observations provided. It can run in parallel by using multiple cores availlable on your computer to run quicker.

Usage

sa_aeme(
  aeme,
  path = ".",
  param,
  model,
  model_controls = NULL,
  FUN_list = NULL,
  ctrl = NULL,
  param_df = NULL
)

Arguments

aeme

aeme; object.

path

filepath; where input files are located relative to `config`.

param

dataframe; of parameters read in from a csv file. Requires the columns c("model", "file", "name", "value", "min", "max", "log")

model

string; for which model to calibrate. Only one model can be passed. Options are c("dy_cd", "glm_aed" and "gotm_wet").

model_controls

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

FUN_list

list of functions; named according to the variables in the vars_sim. Funtions are of the form function(df) which will be used to calculate model fit. If NULL, uses mean absolute error (MAE).

ctrl

list; of controls for sensitivity analysis function created using the create_control function. See create_control for more details.

param_df

dataframe; of parameters to be used in the calibration. Requires the columns c("model", "file", "name", "value", "min", "max"). This is used to restart from a previous calibration.

Value

string of simulation id to be used to read the simulation output.

Examples

if (FALSE) { # \dontrun{
  # Run sensitivity analysis
  tmpdir <- tempdir()
  aeme_dir <- system.file("extdata/lake/", package = "AEME")
  # Copy files from package into tempdir
  file.copy(aeme_dir, tmpdir, recursive = TRUE)
  path <- file.path(tmpdir, "lake")
  aeme <- AEME::yaml_to_aeme(path = path, "aeme.yaml")
  model_controls <- AEME::get_model_controls()
  inf_factor = c("dy_cd" = 1, "glm_aed" = 1, "gotm_wet" = 1)
  outf_factor = c("dy_cd" = 1, "glm_aed" = 1, "gotm_wet" = 1)
  model <- c("glm_aed")
  aeme <- AEME::build_aeme(path = path, aeme = aeme,
                                    model = model, model_controls = model_controls,
                                    inf_factor = inf_factor, ext_elev = 5,
                                    use_bgc = FALSE)

  # Load parameters
  utils::data("aeme_parameters", package = "AEME")
  param <- aeme_parameters |>
    dplyr::filter(file != "wdr")

  # Function to calculate fitness
  fit <- function(df) {
    mean(df$model)
  }

  # Assign function to variable
  FUN_list <- list(HYD_temp = fit)

  # Set up control parameters for surface and bottom temperature
  ctrl <- create_control(method = "sa", N = 2^3, ncore = 2L,
                         parallel = TRUE,
                         vars_sim = list(
                                   surf_temp = list(var = "HYD_temp",
                                                    month = c(10:12, 1:3),
                                                    depth_range = c(0, 2)
                                                    ),
                                   bot_temp = list(var = "HYD_temp",
                                                   month = c(10:12, 1:3),
                                                   depth_range = c(10, 13)
                                                   )
                                   )
  )

  # Run sensitivity analysis AEME model
  ctrl <- sa_aeme(aeme = aeme, path = path, param = param,
                  model = model, ctrl = ctrl, model_controls = model_controls,
                  FUN_list = FUN_list)
} # }