Major Update including linter and styling

.buildlibrary

@@ -1,4 +1,4 @@
-ValidationKey: '2310172334175'
+ValidationKey: '3946000'
 AcceptedWarnings:
 - 'Warning: package ''.*'' was built under R version'
 - 'Warning: namespace ''.*'' is not available and has been replaced'

CITATION.cff

@@ -2,8 +2,8 @@ cff-version: 1.2.0
 message: If you use this software, please cite it using the metadata from this file.
 type: software
 title: 'mrsoil: MadRat Soil Organic Carbon Budget Library'
-version: 1.17.11.9003
-date-released: '2024-01-03'
+version: 2.0.0
+date-released: '2024-01-08'
 abstract: This packages provides functions for soil organic carbon budget for mineral
   soils using the steady-state method (Tier 2) of the 2019 Refinement to the 2006
   IPP Guidelines for National Greenhouse Gas Inventories.

DESCRIPTION

@@ -1,8 +1,8 @@
 Package: mrsoil
 Type: Package
 Title: MadRat Soil Organic Carbon Budget Library
-Version: 1.17.11.9003
-Date: 2024-01-03
+Version: 2.0.0
+Date: 2024-01-08
 Authors@R: c(person("Kristine", "Karstens", email = "karstens@pik-potsdam.de", role = c("aut","cre")),
              person("Jan Philipp", "Dietrich", email = "dietrich@pik-potsdam.de", role = "aut"))
 Description: This packages provides functions for soil organic carbon budget for mineral soils using the steady-state method (Tier 2) of the 2019 Refinement to the 2006 IPP Guidelines for National Greenhouse Gas Inventories.
@@ -11,14 +11,11 @@ Depends:
     magclass(>= 5.15.4),
     madrat(>= 1.86.0),
     mrcommons(>= 0.11.9),
-    mrvalidation(>= 2.4.3),
-    mrmagpie (>= 0.35.0)
+    mrdrivers(>= 1.0.0)
 Imports:
     magpiesets,
     readxl,
-    reshape2,
     lpjclass,
-    ncdf4,
     utils,
     jsonlite
 License: LGPL-3 | file LICENSE

NAMESPACE

@@ -5,29 +5,18 @@ export(toolSoilCarbonCycling)
 import(madrat)
 import(magclass)
 import(mrcommons)
-import(mrmagpie)
-import(mrvalidation)
+import(mrdrivers)
 importFrom(jsonlite,fromJSON)
 importFrom(lpjclass,read.LPJ_input)
 importFrom(madrat,toolSubtypeSelect)
-importFrom(madrat,toolTimeAverage)
 importFrom(madrat,vcat)
 importFrom(magclass,collapseDim)
 importFrom(magclass,dimCode)
-importFrom(magclass,getYears)
 importFrom(magclass,setNames)
-importFrom(magclass,setYears)
-importFrom(magpiesets,Cell2Country)
 importFrom(magpiesets,addLocation)
 importFrom(magpiesets,findset)
-importFrom(ncdf4,nc_open)
-importFrom(ncdf4,ncvar_get)
 importFrom(readxl,read_excel)
-importFrom(reshape2,colsplit)
-importFrom(stats,complete.cases)
 importFrom(stats,quantile)
 importFrom(utils,download.file)
 importFrom(utils,read.csv)
 importFrom(utils,tail)
-importFrom(utils,untar)
-importFrom(utils,write.csv)

R/calcCarbonInputMultiplier.R

@@ -26,10 +26,10 @@ calcCarbonInputMultiplier <- function() {
   inputProp <- NULL
   # get lignin to c and nitrogen to c values for all residues classes
   inputProp   <- mbind(inputProp,
-                       calcOutput("ParamResidues", source = "IPCC+woody", aggregate = FALSE))
+                       calcOutput("ParamResidues", input = "IPCC+woody", aggregate = FALSE))
   # get lignin to c and nitrogen to c values for all manure classes
   inputProp   <- mbind(inputProp,
-                       calcOutput("ParamManure", source = "IPCC", aggregate = FALSE))
+                       calcOutput("ParamManure", input = "IPCC", aggregate = FALSE))
   # get lignin to c and nitrogen to c values for generic input classes
   param     <- readSource("IPCC", subtype = "residues_table5p5b", convert = FALSE)
   generic   <- "Generic value for crops not indicated below"
@@ -49,6 +49,9 @@ calcCarbonInputMultiplier <- function() {
                   setNames(dimSums(weight, dim = 3), "generic"),
                   collapseNames(calcOutput("CarbonManure", aggregate = FALSE)[, "y1995", "c"]))
 
+  getSets(out,    fulldim = FALSE)[1] <- "x.y.iso"
+  getSets(weight, fulldim = FALSE)[1] <- "x.y.iso"
+
   return(list(x            = out,
               weight       = weight,
               unit         = "tC per ha",

R/calcCarbonLitter.R

@@ -27,13 +27,13 @@ calcCarbonLitter <-  function(lpjmlNatveg = "LPJmL4_for_MAgPIE_44ac93de",
 
   # load and convert LPjmL data
   litfallc     <- calcOutput("LPJmL_new", version = lpjmlNatveg, climatetype = climatetype, stage = stage,
-                              subtype = "alitterfallc", aggregate = FALSE, )
+                             subtype = "alitterfallc", aggregate = FALSE, )
   litburnc     <- calcOutput("LPJmL_new", version = lpjmlNatveg, climatetype = climatetype, stage = stage,
-                              subtype = "alitterburnc", aggregate = FALSE)
+                             subtype = "alitterburnc", aggregate = FALSE)
   litfallcWood <- calcOutput("LPJmL_new", version = lpjmlNatveg, climatetype = climatetype, stage = stage,
-                              subtype = "alitterfallc_wood", aggregate = FALSE)
+                             subtype = "alitterfallc_wood", aggregate = FALSE)
   litburncWood <- calcOutput("LPJmL_new", version = lpjmlNatveg, climatetype = climatetype, stage = stage,
-                              subtype = "alitterburnc_wood", aggregate = FALSE)
+                             subtype = "alitterburnc_wood", aggregate = FALSE)
 
   litfallc     <- toolConditionalReplace(litfallc - litburnc,         "<0", 0)
   litfallcWood <- toolConditionalReplace(litfallcWood - litburncWood, "<0", 0)
@@ -61,15 +61,15 @@ calcCarbonLitter <-  function(lpjmlNatveg = "LPJmL4_for_MAgPIE_44ac93de",
                     climatetype = ifelse(fixFpc, "GSWP3-W5E5:historical", climatetype),
                     stage       = ifelse(fixFpc & (mode != "historicalSpinup"), "smoothed", stage),
                     subtype = "fpc", aggregate = FALSE)[, , "fraction natural vegetation", invert = TRUE]
-  if(fixFpc) fpc <- toolFillYears(fpc, years = getYears(out))
+  if (fixFpc) fpc <- toolFillYears(fpc, years = getYears(out))
 
   woodyPfts <- getNames(fpc[, , "grass", invert = TRUE, pmatch = TRUE])
   treeFrac  <- dimSums(fpc[, , woodyPfts], dim = 3)
 
   # Use turnover parameters per pft to calculate leaf fraction in soft tissue litter
   # (soft tissue = fine roots + leaves)
   lpjmlPar       <- readSource("LPJmL_par", subtype = "pft_lpjml4",
-                                convert = FALSE)[, , "sapwood", invert = TRUE, pmatch = TRUE]
+                               convert = FALSE)[, , "sapwood", invert = TRUE, pmatch = TRUE]
   leafFrac   <- collapseDim(lpjmlPar[, , "turnover_root"] / dimSums(lpjmlPar, dim = 3.2))
 
   # Load data from Brovkin et al. on leaf parameters (lignin and nitrogen concentration (per dry matter))
@@ -113,6 +113,9 @@ calcCarbonLitter <-  function(lpjmlNatveg = "LPJmL4_for_MAgPIE_44ac93de",
   weight <- calcOutput("LanduseInitialisation", aggregate = FALSE, cellular = TRUE, years = "y1995")
   weight <- collapseDim(dimSums(weight[, , "crop", invert = TRUE], dim = 3))
 
+  getSets(out,    fulldim = FALSE)[1] <- "x.y.iso"
+  getSets(weight, fulldim = FALSE)[1] <- "x.y.iso"
+
   return(list(x            = out,
               weight       = weight,
               unit         = "tC per ha, tn per tc, tLn per tC",

R/calcCarbonManure.R

@@ -26,7 +26,7 @@ calcCarbonManure <- function() {
   # Cut high input values at 10 tC/ha
   manureInput        <- toolConditionalReplace(manureInput, conditions = "> 10", replaceby = 10)
   # Load parameters for lignin and nitrogen
-  param              <- calcOutput("ParamManure",  source = "IPCC", aggregate = FALSE)
+  param              <- calcOutput("ParamManure",  input = "IPCC", aggregate = FALSE)
 
   kli          <- findset("kli")
   attributes   <- c("c", "LC", "NC")
@@ -36,6 +36,7 @@ calcCarbonManure <- function() {
 
   out[, , "c"]            <- manureInput
   out[, , c("NC", "LC")]  <- param
+  getSets(out, fulldim = FALSE)[1] <- "x.y.iso"
 
   return(list(x            = out,
               weight       = NULL,

R/calcCarbonResidues.R

@@ -17,8 +17,10 @@ calcCarbonResidues <- function() {
   kcr2kres             <- toolGetMapping("mappingCrop2Residue.csv", type = "sectoral", where = "mrcommons")
   residueBiomassBg     <- toolAggregate(residueBiomass, rel = kcr2kres, from = "kcr",
                                         to = "kres", dim = 3.2)[, , "bg"][, , "c"]
-  callResFB            <- function() calcOutput("ResFieldBalancePast", cellular = TRUE,
-                                                products = "kres", aggregate = FALSE)
+  callResFB            <- function() {
+    calcOutput("ResFieldBalancePast", cellular = TRUE,
+               products = "kres", aggregate = FALSE)
+  }
   residueRecyclingAg   <- add_dimension(collapseNames(callResFB()[, , "recycle"][, , "c"]),
                                         dim = 3.1, add = "residues", nm = "ag")
 
@@ -30,7 +32,7 @@ calcCarbonResidues <- function() {
   ## Cut high input values at 10 tC/ha
   residueRecycling     <- toolConditionalReplace(residueRecycling, conditions = "> 10", replaceby = 10)
   # Load parameters for lignin and nitrogen and aggregate them to kres
-  param                <- calcOutput("ParamResidues", aggregate = FALSE, source = "IPCC+woody")
+  param                <- calcOutput("ParamResidues", aggregate = FALSE, input = "IPCC+woody")
   weight               <- collapseNames(dimSums(residueBiomass, dim = "residues"))
   param                <- toolAggregate(param,  weight = weight, rel = kcr2kres, from = "kcr", to = "kres", dim = 3.1)
 
@@ -41,6 +43,7 @@ calcCarbonResidues <- function() {
 
   out[, , "c"]            <- residueRecycling
   out[, , c("LC", "NC")]  <- param
+  getSets(out, fulldim = FALSE)[1] <- "x.y.iso"
 
   return(list(x            = out,
               weight       = NULL,

R/calcDecayFuture.R

@@ -25,7 +25,6 @@
 
 calcDecayFuture <- function(lpjmlNatveg = "LPJmL4_for_MAgPIE_44ac93de",
                             climatetype = "GSWP3-W5E5:historical") {
-
   # Create settings for LPJmL/GCM from version and climatetype argument
   cfg   <- toolClimateInputVersion(lpjmlVersion = lpjmlNatveg,
                                    climatetype  = climatetype)
@@ -45,17 +44,19 @@ calcDecayFuture <- function(lpjmlNatveg = "LPJmL4_for_MAgPIE_44ac93de",
   }
 
   weight <- collapseDim(calcOutput("SoilCarbon", aggregate = FALSE, years = "y1995",
-                        lpjmlNatveg = lpjmlNatveg, climatetype = cfg$baselineHist))
+                                   lpjmlNatveg = lpjmlNatveg, climatetype = cfg$baselineHist))
   weight <- mbind(add_dimension(collapseDim(weight[, , "crop"] + 10^(-10)),
                                 dim = 3.2,  add = "tillage", nm = "fulltill"),
                   add_dimension(collapseDim(weight[, , "crop"] + 10^(-10)),
                                 dim = 3.2,  add = "tillage", nm = "reducedtill"),
                   add_dimension(collapseDim(weight[, , "natveg"] + 10^(-10)),
                                 dim = 3.2,  add = "tillage", nm = "notill"))
 
- return(list(x      = out,
-             weight = weight,
-             unit   = "per yr",
-             description  = "Decay rate for all SOC sub-pool per year",
-             isocountries = FALSE))
+  getSets(out,    fulldim = FALSE)[1] <- "x.y.iso"
+  getSets(weight, fulldim = FALSE)[1] <- "x.y.iso"
+  return(list(x      = out,
+              weight = weight,
+              unit   = "per yr",
+              description  = "Decay rate for all SOC sub-pool per year",
+              isocountries = FALSE))
 }

R/calcDecayRaw.R

@@ -43,11 +43,11 @@ calcDecayRaw <- function(lpjmlNatveg = "LPJmL4_for_MAgPIE_44ac93de",
       # check years and dims
       if (!is.null(out) && (is.null(getYears(out)) || is.null(getYears(tmp)))) {
         tmp <- magpie_expand(tmp, collapseDim(out[, , 1], dim = 3))
-        out <- magpie_expand(out, collapseDim(tmp, dim =3))
+        out <- magpie_expand(out, collapseDim(tmp, dim = 3))
       }
 
       years <- intersect(getYears(tmp), getYears(out))
-      if(!is.null(years)){
+      if (!is.null(years)) {
         out <- out[, years, ]
         tmp <- tmp[, years, ]
       }
@@ -95,24 +95,24 @@ calcDecayRaw <- function(lpjmlNatveg = "LPJmL4_for_MAgPIE_44ac93de",
   cellSandFrac   <- calcOutput("SandFrac", aggregate = FALSE)
 
   # harmonize years
-  .getCommonYears <- function(listOfYearVectors){
-    nullIndex         <- which(sapply(listOfYearVectors, is.null))
-    if(length(nullIndex) != 0) {
+  .getCommonYears <- function(listOfYearVectors) {
+    nullIndex         <- which(vapply(listOfYearVectors, is.null, logical(1)))
+    if (length(nullIndex) != 0) {
       vcat(1, "There are objects with no years (NULL) provided.")
       listOfYearVectors <- listOfYearVectors[-nullIndex]
     }
     commonYears       <- Reduce(intersect, listOfYearVectors)
-    if(length(commonYears) == 0) vcat(0, "There are no common years objects provided.")
+    if (length(commonYears) == 0) vcat(0, "There are no common years objects provided.")
     return(commonYears)
   }
 
   years <- .getCommonYears(list(getYears(cellTempFactor),
                                 getYears(cellTillFactor),
                                 getYears(cellWfactor)))
 
-  if(!is.null(getYears(cellTempFactor))) cellTempFactor <- cellTempFactor[, years, ]
-  if(!is.null(getYears(cellTillFactor))) cellTillFactor <- cellTillFactor[, years, ]
-  if(!is.null(getYears(cellWfactor)))    cellWfactor    <- cellWfactor[, years, ]
+  if (!is.null(getYears(cellTempFactor))) cellTempFactor <- cellTempFactor[, years, ]
+  if (!is.null(getYears(cellTillFactor))) cellTillFactor <- cellTillFactor[, years, ]
+  if (!is.null(getYears(cellWfactor))) cellWfactor    <- cellWfactor[, years, ]
 
   activeDecay    <-  param[, , "kfaca"] * cellWfactor * cellTempFactor * cellTillFactor *
     (param[, , "k3par1"] +  param[, , "k3par2"] * cellSandFrac)
@@ -123,12 +123,13 @@ calcDecayRaw <- function(lpjmlNatveg = "LPJmL4_for_MAgPIE_44ac93de",
   slowDecay    <- .clean(slowDecay,    "slow",    "sub")
   passiveDecay <- .clean(passiveDecay, "passive", "sub")
 
-  if(length(getNames(passiveDecay)) != length(getNames(activeDecay))) {
+  if (length(getNames(passiveDecay)) != length(getNames(activeDecay))) {
     passiveDecay <- dimOrder(magpie_expand(passiveDecay,
                                            collapseDim(activeDecay[, , "rainfed"], keepdim = 3.3)),
-                             perm = c(2,3,1), dim = 3)
+                             perm = c(2, 3, 1), dim = 3)
   }
   decay <- magpiesort(mbind(activeDecay, slowDecay, passiveDecay))
+  getSets(decay, fulldim = FALSE)[1] <- "x.y.iso"
 
   return(list(x      = decay,
               weight = NULL,

R/calcLanduse.R

@@ -23,6 +23,8 @@ calcLanduse <- function(period = "states_1900to2010", output = "total") {
     landuse <- toolLanduseChange(calcOutput("Landuse", period = period, aggregate = FALSE))
   }
 
+  getSets(landuse, fulldim = FALSE)[1] <- "x.y.iso"
+
   return(list(x      = landuse,
               weight = NULL,
               unit   = "Mha",

R/calcParamManure.R

@@ -1,20 +1,19 @@
 #' @title calcParamManure
 #' @description Bring all parameter settings (lignin, nitrogen) for residues together
 #'
-#' @param source      "IPCC"          for IPCC Guideline values
+#' @param input      "IPCC" for IPCC Guideline values
 #' @return List of magpie object with results on global level, unit and description.
 #' @author Kristine Karstens
 #'
 #' @examples
 #' \dontrun{
 #' calcOutput("ParamManure")
 #' }
-
-calcParamManure <- function(source = "IPCC") {
+calcParamManure <- function(input = "IPCC") {
 
   kli  <- magpiesets::findset("kli")
   c2dm <- 0.45
-  if(grepl("IPCC", source)){
+  if (grepl("IPCC", input)) {
 
     param              <- readSource("IPCC", subtype = "manure_table5p5c", convert = FALSE)
 
@@ -26,7 +25,7 @@ calcParamManure <- function(source = "IPCC") {
     out[, , "LC"]  <- param[, , "LC_dm"] / c2dm / 100
 
   } else {
-    stop("'source' unknown.")
+    stop("'input' unknown.")
   }
 
   return(list(x            = out,