Update vignette and analysis

.Rbuildignore

@@ -8,6 +8,7 @@
 ^benchmarking$
 ^Rscripts$
 ^Rold$
+^.idea$
 
 # R-markdown files in the root folder.
 ^.*.ods$

COPYING

@@ -1,4 +1,4 @@
-Copyright 2023, Geocomputation and Earth Observation, University of Bern
+Copyright 2024, Geocomputation and Earth Observation, University of Bern
 
 This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
 

DESCRIPTION

@@ -1,10 +1,10 @@
 Package: rsofun
 Title: The P-Model and BiomeE Modelling Framework
-Version: 4.4.1
+Version: 5.0.0
 Authors@R: c(
             person(
-              family = "Benjamin",
-              given = "Stocker",
+              family = "Stocker",
+              given = "Benjamin",
               email = "benjamin.stocker@gmail.com",
               comment = c(ORCID = "0000-0003-2697-9096"),
               role = c("aut", "cre")),
@@ -26,12 +26,24 @@ Authors@R: c(
                email = "lauramarqueslopez@gmail.com",
                comment = c(ORCID = "0000-0002-3593-5557"),
                role = c("ctb")),
+            person(
+               family = "Marcadella",
+               given = "Mayeul",
+               email = "mayeul.marcadella@gmail.com",
+               comment = c(ORCID = "0000-0001-8555-3808"),
+               role = c("ctb")),
             person(
                family = "Weng",
                given = "Ensheng",
                email = "wengensheng@gmail.com",
                comment = c(ORCID = "0000-0002-1858-4847"),
                role = c("ctb")),
+            person(
+              family = "Bernhard",
+              given = "Fabian",
+              email = "fabian.bernhard@alumni.epfl.ch",
+              role = c("aut"),
+              comment = c(ORCID = "0000-0003-0338-0961")),
             person(given = "Geocomputation and Earth Observation, University of Bern",
                 role = c("cph", "fnd"))
            )

NEWS.md

@@ -1,3 +1,12 @@
+# rsofun v5.0.0
+
+* new BiomeE forcing data matching that of P-model
+  * `prec` is now called `rain`
+  * `rh` is now provided as `vpd`
+  * See `biomee_gs_leuning_drivers` for an example
+* fix Fortran modules leading to segmentation faults using BiomeE model
+* improved documentation
+
 # rsofun v4.4.1
 
 * bugfix Fortran modules and derived types

R/calib_sofun.R

@@ -92,8 +92,7 @@ calib_sofun <- function(
     ...
 ){
   # predefine variables for CRAN check compliance
-  cost <- lower <- upper <- pars <- out <- out_optim <- priors <- setup <- 
-    bt_par <- bt_settings <- NULL
+  lower <- upper <- out_optim <- NULL
 
   # check input variables
   if(missing(obs) | missing(drivers) | missing(settings)){
@@ -166,12 +165,6 @@ calib_sofun <- function(
     setup <- BayesianTools::createBayesianSetup(
       likelihood = function(
     random_par) {
-        # cost(
-        #   par = random_par,
-        #   obs = obs,
-        #   drivers = drivers,
-        #   ...
-        # )
         do.call("cost",
                 list(
                   par = random_par,

R/cost_likelihood_biomee.R

@@ -43,10 +43,10 @@
 #' }
 
 cost_likelihood_biomee <- function(
-  par,
-  obs,
-  drivers,
-  targets
+    par,
+    obs,
+    drivers,
+    targets
 ){
 
   # predefine variables for CRAN check compliance
@@ -57,7 +57,7 @@ cost_likelihood_biomee <- function(
   drivers$params_species[[1]]$LAI_light[]  <- par[2]
   drivers$params_tile[[1]]$tf_base <- par[3]
   drivers$params_tile[[1]]$par_mort <- par[4]
-
+  
   # run model
   df <- runread_biomee_f(
     drivers,
@@ -67,7 +67,7 @@ cost_likelihood_biomee <- function(
 
   # did we spin up
   spin_up <- drivers$params_siml[[1]]$spinup
-
+  
   # drop spinup years if activated
   # see below
   if (spin_up){
@@ -103,7 +103,7 @@ cost_likelihood_biomee <- function(
   }) |>
     unlist() |>
     sum()     # sum log-likelihoods
-              
+
   # trap boundary conditions
   if(is.nan(ll) || is.na(ll) | ll == 0){
     ll <- -Inf

R/cost_likelihood_pmodel.R

@@ -212,7 +212,7 @@ cost_likelihood_pmodel <- function(
   }) |>
     unlist() |>
     sum()
-
+  
   # trap boundary conditions
   if(is.nan(ll) | is.na(ll) | ll == 0){ll <- -Inf}
 

R/cost_rmse_pmodel.R

@@ -73,7 +73,7 @@ cost_rmse_pmodel <- function(
     targets,    
     par_fixed = NULL, # non-calibrated model parameters
     target_weights = NULL, # if using several targets, how are the individual 
-                           # RMSE weighted? named vector
+    #                      # RMSE weighted? named vector
     parallel = FALSE,
     ncores = 2
 ){
@@ -144,10 +144,10 @@ cost_rmse_pmodel <- function(
     }else{
       # Join P-model output and flux observations
       df_flux <- df |>
-      dplyr::filter(sitename %in% flux_sites) |>
-      dplyr::left_join(
-        obs_flux, 
-        by = c('sitename', 'date'))    # observations with missing date are ignored
+        dplyr::filter(sitename %in% flux_sites) |>
+        dplyr::left_join(
+          obs_flux, 
+          by = c('sitename', 'date'))    # observations with missing date are ignored
     }
   }else{
     df_flux <- data.frame()
@@ -170,7 +170,7 @@ cost_rmse_pmodel <- function(
       df_trait <- df |>
         dplyr::filter(sitename %in% trait_sites) |>
         dplyr::group_by(sitename) |>
-          # get growing season average traits
+        # get growing season average traits
         dplyr::summarise(across(ends_with("_mod") & !starts_with('gpp'),
                                 ~ sum(.x * gpp_mod/sum(gpp_mod)),
                                 .names = "{.col}")) |>
@@ -192,7 +192,7 @@ cost_rmse_pmodel <- function(
     }
     if(target %in% colnames(df_trait)){
       error <- c(error, 
-                (df_trait[[target]] - df_trait[[paste0(target, '_mod')]])^2)
+                 (df_trait[[target]] - df_trait[[paste0(target, '_mod')]])^2)
     }
     sqrt(mean(error, na.rm = TRUE))
   }) |>
@@ -204,6 +204,6 @@ cost_rmse_pmodel <- function(
   }else{
     cost <- mean(rmse, na.rm = TRUE)
   }
-
+  
   return(cost)
 }