updated ensemble download for GEE

DESCRIPTION

@@ -1,45 +1,12 @@
 Package: rsofun
-Title: A package for handling the SOFUN model framework for simulating processes
-    in terrestrial ecosystems
-Version: 0.0.0.9000
-Authors@R: c(person("Benjamin", "Stocker", email = "[email protected]", role = c("aut", "cre")),
-    person("Joan", "Maspons", email = "[email protected]", role = c("aut")))
-Description: This package provides functions for all the routine steps in
-    running the SOFUN model, including setup of the model environment, preparation
-    of input files, calibrating model parameters, running the model, reading outputs
-    into R, and evaluating outputs (benchmarking).
+Title: Implements the SOFUN modelling framework for simulating terrestrial processes, including model
+  calibration and benchmarking.
+Version: 0.3.0
+Authors@R: c(person("Benjamin", "Stocker", email = "[email protected]", role = c("aut", "cre")))
+Description: Implements the SOFUN modelling framework for simulating terrestrial processes, including model
+  calibration and benchmarking.
 License: GPL-3
-SystemRequirements: This package uses bash scripts to run NCO (http://
-    nco.sourceforge.net/) and CDO (https://code.mpimet.mpg.de/) commands.
 LazyData: true
-Imports:
-    dplyr,
-    ggplot2,
-    lubridate,
-    Metrics,
-    mgcv,
-    ncdf4,
-    optimr,
-    purrr,
-    readr,
-    rlang,
-    stringr,
-    tidyr,
-    LSD,
-    GenSA,
-Suggests:
-    BayesianTools,
-    caret,
-    gplots,
-    hydroGOF,
-    maps,
-    maptools,
-    neuralnet,
-    nnet,
-    raster,
-    sp,
-    testthat,
-    knitr,
-    rmarkdown
-RoxygenNote: 7.0.2
+Depends: dplyr, purrr, lubridate, tidyr, raster, lubridate, stringi, sp, gensa, stringr, rland, readr
+RoxygenNote: 7.1.0
 VignetteBuilder: knitr

R/collect_drivers_sofun.R

@@ -3,25 +3,29 @@
 #' Collect all drivers for site-level simulations into a nested data frame with one row for each site
 #'
 #' @param settings A named list containing the simulation settings (see vignette_rsofun.pdf for more information and examples).
-#' @param forcing A data frame containing the model forcing for each model time step. 
+#' @param meteo A data nested data frame with rows for each site and meteo forcing data time series nested inside a column named \code{"data"}
+#' @param fapar A data nested data frame with rows for each site and fAPAR forcing data time series nested inside a column named \code{"data"}
 #' @param df_soiltexture
 #'
 #' @return
 #' @export
 #'
 #' @examples mod <- collect_drivers_sofun( settings = settings, forcing, df_soiltexture )
 #' 
-collect_drivers_sofun <- function( settings, forcing, df_soiltexture ){
+collect_drivers_sofun <- function( settings, meteo, fapar, df_soiltexture ){
 
   ## create mega-df containing all forcing data and parameters that vary by site (not model parameters!)
   names_metainfo <- names(settings)[-which(names(settings) %in% c("sitename", "params_siml"))]
   df_mega <- settings %>% 
     tidyr::nest(siteinfo = names_metainfo) %>% 
     left_join(
-      forcing %>% 
-        group_by(sitename) %>% 
-        tidyr::nest() %>% 
-        rename(forcing = data),
+      meteo %>% 
+        rename(meteo = data),
+      by = "sitename"
+    ) %>% 
+    left_join(
+      fapar %>% 
+        rename(fapar = data),
       by = "sitename"
     ) %>% 
     mutate(df_soiltexture = purrr::map(as.list(seq(nrow(.))), ~return(df_soiltexture)))

R/prepare_setup_sofun.R

@@ -44,7 +44,8 @@ prepare_setup_sofun <- function( siteinfo, params_siml ){
     dplyr::mutate(tmp = 1) %>% 
     dplyr::right_join(mutate(siteinfo, tmp = 1), by = "tmp") %>% 
     dplyr::select(names(siteinfo), names(params_siml)) %>% 
-    dplyr::rename(nyeartrend = years_data, firstyeartrend = year_start) %>% 
+    dplyr::mutate(nyeartrend = year_end - year_start + 1) %>%
+    dplyr::rename(firstyeartrend = year_start) %>% 
     tidyr::nest(params_siml = c(names(params_siml), "firstyeartrend", "nyeartrend"))
 
   return(siteinfo)

R/run_sofun_f_bysite.R

@@ -116,11 +116,6 @@ run_sofun_f_bysite <- function( sitename, params_siml, siteinfo, forcing, df_soi
       calc_aet_fapar_vpd        = as.logical(params_siml$calc_aet_fapar_vpd),
       in_ppfd                   = as.logical(params_siml$in_ppfd),
       in_netrad                 = as.logical(params_siml$in_netrad),
-      const_clim_year           = as.integer(params_siml$const_clim_year),
-      const_lu_year             = as.integer(params_siml$const_lu_year),
-      const_co2_year            = as.integer(params_siml$const_co2_year),
-      const_ndep_year           = as.integer(params_siml$const_ndep_year),
-      const_nfert_year          = as.integer(params_siml$const_nfert_year),
       outdt                     = as.integer(params_siml$outdt),
       ltre                      = as.logical(params_siml$ltre),
       ltne                      = as.logical(params_siml$ltne),