Read calibration output
Usage
read_simulation_output(
ctrl = NULL,
file_name,
file_dir,
file_type = "db",
sim_id = NULL,
type
)
read_calib(
ctrl = NULL,
file_name,
file_dir,
file_type = "db",
sim_id = NULL,
type
)Arguments
- ctrl
list; of controls for sensitivity analysis function created using the
create_controlfunction. See create_control for more details.- file_name
The name of the output file. If
ctrlis provided, this argument is ignored.- file_dir
The directory of the output file. If
ctrlis provided, this argument is ignored.- file_type
string; file type to write the output to. Options are
c("csv", "db"). Defaults to "db".- sim_id
A vector of simulation IDs to read. If NULL, all simulations are read.
- type
A character string indicating the type of simulation. One of "calib", "sa", or "all". If missing, the type is inferred from the
ctrlargument. If type is provided it overrides thectrl$methodvalue.
Examples
aeme_file <- system.file("extdata/aeme.rds", package = "AEME")
aeme <- readRDS(aeme_file)
model_controls <- AEME::get_model_controls()
model <- c("glm_aed", "gotm_wet")
path <- "aeme"
aeme <- AEME::build_aeme(aeme = aeme, model = model, path = path,
model_controls = model_controls, ext_elev = 5) |>
AEME::run_aeme()
#> Warning: ! `SIL_rsi`: SIL_rsi is constant across all rows — this may be a placeholder
#> value.
#> ℹ Check raw data or unit conversion for this variable.
#>
#> ── Calculating water balance ──
#>
#> Resolving water level
#> ℹ Using observed water level
#> ! Missing values in observed water level
#> ℹ Estimating surface water temperature
#> ✔ Estimating surface water temperature [7ms]
#>
#> Estimating lake water levels for glm_aed
#> ℹ Optimizing parameters for water balance
#> ✔ Optimization Complete: C = 0.3343, h_inv = 23.4915, Final RMSE = 0.1431
#> Estimating lake water levels for gotm_wet
#> ℹ Optimizing parameters for water balance
#> ✔ Optimization Complete: C = 0.334, h_inv = 23.4829, Final RMSE = 0.1472
#> ℹ Correcting water balance using estimated outflows (method = 2).
#>
#> ── Building GLM-AED for lake wainamu ──
#>
#> ℹ Building GOTM-WET model for lake wainamu
#> ✔ GOTM YAML validation completed - no issues detected.
#> ✔ GLM nml validation completed - no issues detected.
#> ℹ Running models... (Have you tried parallelizing?) [2026-06-16 23:56:50]
#> → GLM-AED running... [2026-06-16 23:56:50]
#> ✔ GLM-AED run successful! [2026-06-16 23:56:50]
#> → GOTM-WET running... [2026-06-16 23:56:50]
#> ✔ GOTM-WET run successful! [2026-06-16 23:56:50]
#> ✔ Model run complete! [2026-06-16 23:56:50]
#> ! The following variables are not available in model gotm_wet: RAD_extc
data("aeme_parameters", package = "AEME")
param <- aeme_parameters
# Function to calculate fitness
nse <- function(df) {
# Calculate Nash-Sutcliffe Efficiency
nse <- 1 - (sum((df$obs - df$model)^2) / sum((df$obs - mean(df$obs))^2))
-1 * nse
}
FUN_list <- list(HYD_temp = nse, LKE_lvlwtr = nse)
ctrl <- create_control(method = "calib", NP = 10, itermax = 20, ncore = 2,
parallel = TRUE, file_type = "db",
file_name = "results.db")
vars_sim <- c("HYD_temp", "LKE_lvlwtr")
weights <- c("HYD_temp" = 1, "LKE_lvlwtr" = 1)
# Calibrate AEME model
sim_id <- calib_aeme(aeme = aeme, model = model, path = path,
param = param, FUN_list = FUN_list, ctrl = ctrl,
vars_sim = vars_sim, weights = weights)
#> ℹ Variables not found: `LKE_lvlwtr`.
#> Adding them to model_controls.
#> ℹ Extracting indices for "glm_aed" modelled variables [2026-06-16 23:56:51]
#> ✔ Indices extracted for "glm_aed" modelled variables [2026-06-16 23:56:52]
#> ℹ Using 2 cores for parallel calibration for "glm_aed".
#> → Starting generation 1/2, 10 members. [2026-06-16 23:56:53]
#> Parameter summary for generation 1:
#> light/Kw MET_wndspd MET_radswd mixing/coef_mix_conv
#> mean 2.771 1.0040 0.9956 0.14960
#> median 2.563 0.9955 0.9888 0.14690
#> sd 1.655 0.1795 0.1833 0.03246
#> mixing/coef_wind_stir mixing/coef_mix_shear mixing/coef_mix_turb
#> mean 0.25030 0.14970 0.4417
#> median 0.24840 0.15350 0.4362
#> sd 0.02996 0.03067 0.1525
#> mixing/coef_mix_hyp outflow inflow
#> mean 0.6005 1.4710 1.4690
#> median 0.5977 1.5100 1.5050
#> sd 0.1182 0.5938 0.6087
#> ✔ Completed generation 1/2
#> for "glm_aed". [2026-06-16 23:57:10]
#> Best fit: 27.5 (sd: 3299.1) Parameters: [ 3.66, 1.08, 0.711, 0.101, 0.242,
#> 0.113, 0.561, 0.459, 0.584, and 0.583 ]
#> Writing output for generation 1 to results.db with sim ID: "45819_glmaed_C_003"
#> [2026-06-16 23:57:10]
#> ℹ Survival rate: 0.8
#> → Starting generation 2/2, 10 members. [2026-06-16 23:57:10]
#> Parameter summary for generation 2:
#> light/Kw MET_wndspd MET_radswd mixing/coef_mix_conv
#> mean 3.3510 1.0310 0.9118 0.11560
#> median 3.6040 1.0720 0.8383 0.10810
#> sd 0.7859 0.0841 0.2244 0.01729
#> mixing/coef_wind_stir mixing/coef_mix_shear mixing/coef_mix_turb
#> mean 0.2321 0.13690 0.4558
#> median 0.2396 0.11760 0.5304
#> sd 0.0154 0.03464 0.1640
#> mixing/coef_mix_hyp outflow inflow
#> mean 0.5487 0.8769 0.9280
#> median 0.4797 0.6845 0.6614
#> sd 0.1382 0.3899 0.4792
#> Writing output for generation 2 to results.db with sim ID: "45819_glmaed_C_003"
#> [2026-06-16 23:57:18]
#> ✔ Completed generation 2/2
#> for "glm_aed". [2026-06-16 23:57:19]
#> Best fit: 6.4 (sd: 863.39)
#> ℹ Survival rate: 1
#> ℹ Extracting indices for "gotm_wet" modelled variables [2026-06-16 23:57:19]
#> ✔ Indices extracted for "gotm_wet" modelled variables [2026-06-16 23:57:20]
#> ℹ Using 2 cores for parallel calibration for "gotm_wet".
#> → Starting generation 1/2, 10 members. [2026-06-16 23:57:21]
#> Parameter summary for generation 1:
#> turbulence/turb_param/k_min light_extinction/A/constant_value
#> mean 4.939e-06 0.52250
#> median 4.785e-06 0.52220
#> sd 3.091e-06 0.08191
#> light_extinction/g1/constant_value light_extinction/g2/constant_value
#> mean 0.59090 1.3690
#> median 0.59820 1.4530
#> sd 0.08894 0.8391
#> MET_wndspd MET_radswd outflow inflow
#> mean 0.9938 1.0010 1.4950 1.5010
#> median 0.9737 0.9877 1.5180 1.4610
#> sd 0.1830 0.1722 0.6088 0.5899
#> ✔ Completed generation 1/2
#> for "gotm_wet". [2026-06-16 23:57:38]
#> Best fit: 937 (sd: 20559) Parameters: [ 4.04e-06, 0.613, 0.543, 0.588, 0.83,
#> 0.866, 2.21, and 2.08 ]
#> Writing output for generation 1 to results.db with sim ID:
#> "45819_gotmwet_C_003" [2026-06-16 23:57:38]
#> ℹ Survival rate: 0.7
#> → Starting generation 2/2, 10 members. [2026-06-16 23:57:38]
#> Parameter summary for generation 2:
#> turbulence/turb_param/k_min light_extinction/A/constant_value
#> mean 5.378e-06 0.54500
#> median 5.879e-06 0.51500
#> sd 2.225e-06 0.07573
#> light_extinction/g1/constant_value light_extinction/g2/constant_value
#> mean 0.58260 0.4119
#> median 0.60160 0.2657
#> sd 0.04975 0.3112
#> MET_wndspd MET_radswd outflow inflow
#> mean 0.9382 1.0340 1.7830 1.9600
#> median 0.9609 1.1460 1.5950 1.8500
#> sd 0.1717 0.2115 0.4603 0.3688
#> Writing output for generation 2 to results.db with sim ID:
#> "45819_gotmwet_C_003" [2026-06-16 23:57:48]
#> ✔ Completed generation 2/2
#> for "gotm_wet". [2026-06-16 23:57:48]
#> Best fit: 55.4 (sd: 6753.9)
#> ℹ Survival rate: 1
# Read calibration output
calib <- read_calib(sim_id = sim_id, ctrl = ctrl)