Plot calibration results
Usage
plot_calib(
calib,
fit_col = "fit",
nrow = 2,
base_size = 8,
return_pars = FALSE,
log_y = TRUE,
na_value = deprecated()
)Arguments
- calib
A list with the calibration results loaded using
read_calib.- fit_col
character; name of column containing fit values. Default is
"fit".- nrow
integer; number of rows in plot
- base_size
numeric; base size for theme
- return_pars
logical; return parameter values
- log_y
logical; use log scale on y-axis. Default is
TRUE.- na_value
![[Deprecated]](figures/lifecycle-deprecated.svg)
Numeric. Penalty value
substituted for NAfit values, this is no longer needed as NA values are now written to simulation_data in output of calib_aeme() and sa_aeme(). The argument will be removed in a future version.
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 23:55:27]
#> → GLM-AED running... [2026-06-16 23:55:27]
#> ✔ GLM-AED run successful! [2026-06-16 23:55:27]
#> → GOTM-WET running... [2026-06-16 23:55:27]
#> ✔ GOTM-WET run successful! [2026-06-16 23:55:28]
#> ✔ Model run complete! [2026-06-16 23:55:28]
#> ! 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 23:55:29]
#> ✔ Indices extracted for "glm_aed" modelled variables [2026-06-16 23:55:30]
#> ℹ Using 2 cores for parallel calibration for "glm_aed".
#> → Starting generation 1/2, 10 members. [2026-06-16 23:55:30]
#> Parameter summary for generation 1:
#> light/Kw MET_wndspd MET_radswd mixing/coef_mix_conv
#> mean 2.807 1.0000 0.9927 0.15040
#> median 2.845 0.9934 1.0150 0.15200
#> sd 1.531 0.1745 0.1880 0.03004
#> mixing/coef_wind_stir mixing/coef_mix_shear mixing/coef_mix_turb
#> mean 0.24990 0.14960 0.4450
#> median 0.24840 0.14840 0.4710
#> sd 0.02969 0.03118 0.1532
#> mixing/coef_mix_hyp outflow inflow
#> mean 0.6024 1.5160 1.5050
#> median 0.6122 1.5570 1.5060
#> sd 0.1230 0.5903 0.6052
#> ✔ Completed generation 1/2
#> for "glm_aed". [2026-06-16 23:55:46]
#> Best fit: 1420 (sd: 2675.9) Parameters: [ 2.7, 0.859, 0.886, 0.123, 0.218,
#> 0.112, 0.515, 0.637, 1.19, and 0.61 ]
#> Writing output for generation 1 to results.db with sim ID: "45819_glmaed_C_002"
#> [2026-06-16 23:55:46]
#> ℹ Survival rate: 0.6
#> → Starting generation 2/2, 10 members. [2026-06-16 23:55:47]
#> Parameter summary for generation 2:
#> light/Kw MET_wndspd MET_radswd mixing/coef_mix_conv
#> mean 4.3280 1.208 1.1730 0.1496
#> median 4.4090 1.259 1.2460 0.1506
#> sd 0.7157 0.139 0.1884 0.0182
#> mixing/coef_wind_stir mixing/coef_mix_shear mixing/coef_mix_turb
#> mean 0.2386 0.12760 0.43260
#> median 0.2359 0.12720 0.45850
#> sd 0.0266 0.02061 0.08927
#> mixing/coef_mix_hyp outflow inflow
#> mean 0.71740 1.9810 2.0160
#> median 0.72050 2.0770 2.2670
#> sd 0.03507 0.3487 0.6639
#> Writing output for generation 2 to results.db with sim ID: "45819_glmaed_C_002"
#> [2026-06-16 23:55:55]
#> ✔ Completed generation 2/2
#> for "glm_aed". [2026-06-16 23:55:55]
#> Best fit: 28 (sd: 739.72)
#> ℹ Survival rate: 0.8
#> ℹ Extracting indices for "gotm_wet" modelled variables [2026-06-16 23:55:55]
#> ✔ Indices extracted for "gotm_wet" modelled variables [2026-06-16 23:55:57]
#> ℹ Using 2 cores for parallel calibration for "gotm_wet".
#> → Starting generation 1/2, 10 members. [2026-06-16 23:55:57]
#> Parameter summary for generation 1:
#> turbulence/turb_param/k_min light_extinction/A/constant_value
#> mean 5.038e-06 0.52570
#> median 5.175e-06 0.52820
#> sd 2.989e-06 0.08054
#> light_extinction/g1/constant_value light_extinction/g2/constant_value
#> mean 0.59190 1.393
#> median 0.58270 1.370
#> sd 0.09116 0.828
#> MET_wndspd MET_radswd outflow inflow
#> mean 1.0030 1.0000 1.4720 1.5090
#> median 1.0070 0.9877 1.4180 1.5870
#> sd 0.1778 0.1822 0.6385 0.5825
#> ✔ Completed generation 1/2
#> for "gotm_wet". [2026-06-16 23:56:15]
#> Best fit: 124 (sd: 19366) Parameters: [ 4.43e-06, 0.439, 0.48, 1.74, 1.04,
#> 0.947, 1.88, and 1.84 ]
#> Writing output for generation 1 to results.db with sim ID:
#> "45819_gotmwet_C_002" [2026-06-16 23:56:15]
#> ℹ Survival rate: 0.6
#> → Starting generation 2/2, 10 members. [2026-06-16 23:56:15]
#> Parameter summary for generation 2:
#> turbulence/turb_param/k_min light_extinction/A/constant_value
#> mean 4.646e-06 0.48530
#> median 4.370e-06 0.47040
#> sd 1.142e-06 0.07295
#> light_extinction/g1/constant_value light_extinction/g2/constant_value
#> mean 0.50930 1.5440
#> median 0.49050 1.5980
#> sd 0.06984 0.8177
#> MET_wndspd MET_radswd outflow inflow
#> mean 1.05100 0.9768 1.7820 1.7300
#> median 1.03800 0.9811 1.8290 1.8270
#> sd 0.06014 0.1248 0.3004 0.3341
#> Writing output for generation 2 to results.db with sim ID:
#> "45819_gotmwet_C_002" [2026-06-16 23:56:25]
#> ✔ Completed generation 2/2
#> for "gotm_wet". [2026-06-16 23:56:25]
#> Best fit: 22.9 (sd: 2731)
#> ℹ Survival rate: 0.9
# Read calibration output
calib <- read_calib(sim_id = sim_id, ctrl = ctrl)
plist <- plot_calib(calib = calib)
# Dotty plot
plist$dotty
#> Warning: Removed 60 rows containing missing values or values outside the scale range
#> (`geom_point()`).
#> Warning: Removed 40 rows containing missing values or values outside the scale range
#> (`geom_point()`).
# Convergence plot
plist$convergence
# Histogram plot
plist$histogram
