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$methodvalue.
Examples
aeme_file <- system.file("extdata/aeme.rds", package = "AEME")
aeme <- readRDS(aeme_file)
model_controls <- AEME::get_model_controls()
model <- c("glm_aed", "gotm_wet")
path <- "aeme"
aeme <- AEME::build_aeme(aeme = aeme, model = model, path = path,
model_controls = model_controls, ext_elev = 5) |>
AEME::run_aeme()
#> ℹ Using observed water level
#> ℹ No missing values in observed water level. Using observed water level
#> ℹ Correcting water balance using estimated outflows (method = 2).
#> ℹ Calculating lake level using lake depth and a sinisoidal function.
#> ℹ Building GLM-AED for lake wainamu
#> ℹ Building GOTM-WET model for lake wainamu
#> ✔ GOTM YAML validation completed - no issues detected.
#> ✔ GLM nml validation completed - no issues detected.
#> ℹ Running models... (Have you tried parallelizing?) [2026-03-04 03:04:03]
#> → GLM-AED running... [2026-03-04 03:04:03]
#> ✔ GLM-AED run successful! [2026-03-04 03:04:03]
#> → GOTM-WET running... [2026-03-04 03:04:03]
#> ✔ GOTM-WET run successful! [2026-03-04 03:04:04]
#> ✔ Model run complete! [2026-03-04 03:04:04]
#> ! The following variables are not available in model gotm_wet: RAD_extc
#> ! The following variables are not available in model gotm_wet: RAD_extc
data("aeme_parameters", package = "AEME")
param <- aeme_parameters
# Function to calculate fitness
nse <- function(df) {
# Calculate Nash-Sutcliffe Efficiency
nse <- 1 - (sum((df$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 [2026-03-04 03:04:05]
#> ✔ Indices extracted for "glm_aed" modelled variables [2026-03-04 03:04:06]
#> ℹ Using 2 cores for parallel calibration for "glm_aed".
#> → Starting generation 1/2, 10 members. [2026-03-04 03:04:07]
#> Parameter summary for generation 1:
#> light/Kw MET_wndspd MET_radswd mixing/coef_mix_conv
#> mean 2.861 0.9918 1.0000 0.15010
#> median 2.764 0.9815 0.9993 0.15030
#> sd 1.612 0.1869 0.1926 0.02925
#> mixing/coef_wind_stir mixing/coef_mix_shear mixing/coef_mix_turb
#> mean 0.24920 0.14830 0.4551
#> median 0.24780 0.15090 0.4594
#> sd 0.02897 0.03033 0.1553
#> mixing/coef_mix_hyp outflow inflow
#> mean 0.5934 1.4660 1.5450
#> median 0.5891 1.4040 1.5750
#> sd 0.1240 0.6184 0.6141
#> ✔ Completed generation 1/2
#> for "glm_aed". [2026-03-04 03:04:21]
#> Best fit: 263 (sd: 4032.3) Parameters: [ 3.05, 1.07, 1.27, 0.106, 0.253, 0.196,
#> 0.217, 0.646, 1.3, and 1.25 ]
#> Writing output for generation 1 to results.db with sim ID: "45819_glmaed_C_003"
#> [2026-03-04 03:04:21]
#> ℹ Survival rate: 0.7
#> → Starting generation 2/2, 10 members. [2026-03-04 03:04:22]
#> Parameter summary for generation 2:
#> light/Kw MET_wndspd MET_radswd mixing/coef_mix_conv
#> mean 1.787 0.9291 1.1160 0.15580
#> median 1.554 0.9214 1.1440 0.15350
#> sd 1.422 0.1569 0.1525 0.03803
#> mixing/coef_wind_stir mixing/coef_mix_shear mixing/coef_mix_turb
#> mean 0.260400 0.186300 0.4510
#> median 0.258500 0.186800 0.4445
#> sd 0.009843 0.008991 0.1460
#> mixing/coef_mix_hyp outflow inflow
#> mean 0.65600 1.4890 1.6860
#> median 0.68410 1.5320 1.7260
#> sd 0.09622 0.3176 0.5123
#> Writing output for generation 2 to results.db with sim ID: "45819_glmaed_C_003"
#> [2026-03-04 03:04:30]
#> ✔ Completed generation 2/2
#> for "glm_aed". [2026-03-04 03:04:30]
#> Best fit: 18.6 (sd: 2756.6)
#> ℹ Survival rate: 1
#> ℹ Extracting indices for "gotm_wet" modelled variables [2026-03-04 03:04:30]
#> ✔ Indices extracted for "gotm_wet" modelled variables [2026-03-04 03:04:31]
#> ℹ Using 2 cores for parallel calibration for "gotm_wet".
#> → Starting generation 1/2, 10 members. [2026-03-04 03:04:32]
#> Parameter summary for generation 1:
#> turbulence/turb_param/k_min light_extinction/A/constant_value
#> mean 4.940e-06 0.52720
#> median 4.905e-06 0.52790
#> sd 3.167e-06 0.08187
#> light_extinction/g1/constant_value light_extinction/g2/constant_value
#> mean 0.59090 1.3460
#> median 0.60150 1.4500
#> sd 0.08696 0.8097
#> MET_wndspd MET_radswd outflow inflow
#> mean 1.0030 0.9975 1.4950 1.5140
#> median 0.9910 0.9961 1.4720 1.4320
#> sd 0.1803 0.1845 0.6073 0.6017
#> ✔ Completed generation 1/2
#> for "gotm_wet". [2026-03-04 03:04:50]
#> Best fit: 108 (sd: 9490.8) Parameters: [ 1.52e-06, 0.448, 0.483, 0.854, 0.829,
#> 0.97, 2.21, and 2.28 ]
#> Writing output for generation 1 to results.db with sim ID:
#> "45819_gotmwet_C_003" [2026-03-04 03:04:50]
#> ℹ Survival rate: 0.8
#> → Starting generation 2/2, 10 members. [2026-03-04 03:04:50]
#> Parameter summary for generation 2:
#> turbulence/turb_param/k_min light_extinction/A/constant_value
#> mean 1.881e-06 0.48090
#> median 1.743e-06 0.47080
#> sd 4.958e-07 0.06674
#> light_extinction/g1/constant_value light_extinction/g2/constant_value
#> mean 0.50360 1.1670
#> median 0.49510 1.0440
#> sd 0.04614 0.7084
#> MET_wndspd MET_radswd outflow inflow
#> mean 0.83980 0.9083 1.8010 1.8990
#> median 0.84240 0.9112 1.8290 2.0430
#> sd 0.05328 0.1094 0.6452 0.6382
#> Writing output for generation 2 to results.db with sim ID:
#> "45819_gotmwet_C_003" [2026-03-04 03:05:00]
#> ✔ Completed generation 2/2
#> for "gotm_wet". [2026-03-04 03:05:00]
#> Best fit: 61.6 (sd: 1935.1)
#> ℹ Survival rate: 1
# Read calibration output
calib <- read_calib(sim_id = sim_id, ctrl = ctrl)