Merge pull request #43 from tscheypidi/hardcore

adjusted package to mrcommons split

.buildlibrary

@@ -1,8 +1,8 @@
-ValidationKey: '29200821'
+ValidationKey: '29386880'
 AutocreateReadme: yes
 AcceptedWarnings:
-- 'Warning: package ''.*'' was built under R version'
-- 'Warning: namespace ''.*'' is not available and has been replaced'
+- 'Warning: package .* was built under R version'
+- 'Warning: namespace .* is not available and has been replaced'
 AcceptedNotes:
 - unable to verify current time
 - includes the non-default packages

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: 'mrmagpie: madrat based MAgPIE Input Data Library'
-version: 1.47.1
-date-released: '2024-05-08'
+version: 1.48.0
+date-released: '2024-05-13'
 abstract: Provides functions for MAgPIE country and cellular input data generation.
 authors:
 - family-names: Karstens

DESCRIPTION

@@ -1,8 +1,8 @@
 Type: Package
 Package: mrmagpie
 Title: madrat based MAgPIE Input Data Library
-Version: 1.47.1
-Date: 2024-05-08
+Version: 1.48.0
+Date: 2024-05-13
 Authors@R: c(
     person("Kristine", "Karstens", , "[email protected]", role = c("aut", "cre")),
     person("Jan Philipp", "Dietrich", , "[email protected]", role = "aut"),
@@ -25,10 +25,11 @@ BugReports: https://github.com/pik-piam/mrmagpie/issues
 Depends:
     madrat (>= 2.8.0),
     magclass (>= 3.17),
-    mrcommons (>= 1.37.0),
-    mrland (>= 0.51.0),
+    mrcommons (>= 1.41.0),
+    mrlandcore (>= 1.0.0),
+    mrland (>= 0.59.0),
     mrsoil (>= 2.0.0),
-    mrwater (>= 1.11.0),
+    mrwater (>= 1.13.0),
     R (>= 3.5.0)
 Imports:
     abind,
@@ -37,9 +38,9 @@ Imports:
     dplyr,
     ggplot2,
     lpjclass,
-    luplot (>= 3.56.0),
+    luplot (>= 3.64.0),
     magpiesets,
-    mstools,
+    mstools (>= 0.6.0),
     ncdf4,
     pbapply,
     raster,

NAMESPACE

@@ -22,6 +22,7 @@ import(magclass)
 import(magpiesets)
 import(mrcommons)
 import(mrland)
+import(mrlandcore)
 import(mrsoil)
 import(mrwater)
 import(mstools)
@@ -71,15 +72,15 @@ importFrom(magclass,where)
 importFrom(magclass,wrap)
 importFrom(magpiesets,addLocation)
 importFrom(magpiesets,findset)
-importFrom(mrcommons,toolCell2isoCell)
-importFrom(mrcommons,toolCoord2Isocell)
-importFrom(mrcommons,toolCoord2Isocoord)
-importFrom(mrcommons,toolGetMappingCoord2Country)
-importFrom(mrcommons,toolHarmonize2Baseline)
-importFrom(mrcommons,toolIso2CellCountries)
-importFrom(mrcommons,toolLPJmLVersion)
 importFrom(mrland,spatial_header)
+importFrom(mrlandcore,toolLPJmLVersion)
+importFrom(mstools,toolCell2isoCell)
+importFrom(mstools,toolCoord2Isocell)
+importFrom(mstools,toolCoord2Isocoord)
+importFrom(mstools,toolGetMappingCoord2Country)
+importFrom(mstools,toolHarmonize2Baseline)
 importFrom(mstools,toolHoldConstant)
+importFrom(mstools,toolIso2CellCountries)
 importFrom(ncdf4,nc_open)
 importFrom(ncdf4,ncvar_get)
 importFrom(pbapply,pbapply)

R/calcAfforestationMask.R

@@ -11,31 +11,32 @@
 #' }
 #'
 #' @importFrom magclass as.magpie
+#' @importFrom mstools toolGetMappingCoord2Country toolCoord2Isocell
 
 calcAfforestationMask <- function(subtype, cells = "lpjcell") {
 
   if (subtype == "unrestricted") {
     r <- terra::rast(res = 0.5, vals = 1)
-  } else if (subtype == "noboreal") { #Exclude boreal regions > 50deg N
+  } else if (subtype == "noboreal") { # Exclude boreal regions > 50deg N
     r <- terra::rast(res = 0.5, vals = 1)
     lat <- terra::init(r, "y") |> terra::mask(r)
-    r <- terra::mask(r, lat>50, maskvalue=TRUE, updatevalue=0)
-  } else if (subtype == "onlytropical") { #only tropical areas between 20deg S and 20deg N
+    r <- terra::mask(r, lat > 50, maskvalue = TRUE, updatevalue = 0)
+  } else if (subtype == "onlytropical") { # only tropical areas between 20deg S and 20deg N
     r <- terra::rast(res = 0.5, vals = 1)
     lat <- terra::init(r, "y") |> terra::mask(r)
-    r <- terra::mask(r, lat > 20, maskvalue=TRUE, updatevalue=0)
-    r <- terra::mask(r, lat < -20, maskvalue=TRUE, updatevalue=0)
+    r <- terra::mask(r, lat > 20, maskvalue = TRUE, updatevalue = 0)
+    r <- terra::mask(r, lat < -20, maskvalue = TRUE, updatevalue = 0)
   }
 
 
   # get spatial mapping
-  map <- mrcommons::toolGetMappingCoord2Country(pretty = TRUE)
+  map <- toolGetMappingCoord2Country(pretty = TRUE)
   # transform raster to magpie object
   x <- as.magpie(terra::extract(r, map[c("lon", "lat")])[, -1], spatial = 1)
   dimnames(x) <- list("x.y.iso" = paste(map$coords, map$iso, sep = "."), "t" = NULL, "d3" = NULL)
 
   if (cells == "magpiecell") {
-    x <- mrcommons::toolCoord2Isocell(x, cells = cells)
+    x <- toolCoord2Isocell(x, cells = cells)
   }
 
   weight <- calcOutput("LandArea", aggregate = FALSE, cells = cells)

R/calcAgeClassDistribution.R

@@ -12,16 +12,16 @@
 #' }
 #'
 #' @importFrom magclass where
+#' @importFrom mstools toolCoord2Isocell
 
 calcAgeClassDistribution <- function(cells = "lpjcell") {
-
   # Cell fraction from poulter data set
   poulterDataset <- readSource("GFAD", convert = "onlycorrect")
 
   # Calculate cellarea
   mapping <- toolGetMappingCoord2Country()
   cb <- toolGetMapping("LPJ_CellBelongingsToCountries.csv",
-                      type = "cell", where = "mrcommons")
+                       type = "cell", where = "mrcommons")
   cellArea <- (111e3 * 0.5) * (111e3 * 0.5) * cos(cb$lat / 180 * pi)
   cellArea <- as.magpie(cellArea, spatial = 1)
   getItems(cellArea, dim = 1, raw = TRUE) <- paste(mapping$coords, mapping$iso, sep = ".")

R/calcAreaEquippedForIrrigation.R

@@ -22,6 +22,7 @@
 #' calcOutput("AreaEquippedForIrrigation", source = "LUH2v2", cellular = TRUE, aggregate = FALSE)
 #' }
 #' @importFrom magpiesets findset
+#' @importFrom mstools toolCoord2Isocell
 #'
 #' @export
 

R/calcAvlLandSi.R

@@ -13,7 +13,7 @@
 #'
 #' @importFrom madrat readSource calcOutput
 #' @importFrom magclass dimSums getCells getYears getNames mbind collapseDim
-#' @importFrom mrcommons toolCoord2Isocell toolGetMappingCoord2Country
+#' @importFrom mstools toolCoord2Isocell toolGetMappingCoord2Country
 #' @importFrom magpiesets addLocation
 #'
 
@@ -69,7 +69,7 @@ calcAvlLandSi <- function(cells = "lpjcell") {
               weight = NULL,
               unit = "Mha",
               description = paste0("si and nsi0 areas based on Ramankutty",
-                                  "suitability information and LUH area",
-                                  "information from initialization year"),
+                                   "suitability information and LUH area",
+                                   "information from initialization year"),
               isocountries = FALSE))
 }

R/calcDegradationYieldReduction.R

@@ -11,11 +11,11 @@
 #' calcOutput("DegradationYieldReduction", aggregate = FALSE)
 #' }
 #' @importFrom magpiesets findset
-#'
+#' @importFrom mstools toolGetMappingCoord2Country toolCoord2Isocell
 
 calcDegradationYieldReduction <- function(cells = "lpjcell") {
   # create a dummy data set, which is later used to define yield impacts of land degradation
-  coordMapping <- mrcommons::toolGetMappingCoord2Country()
+  coordMapping <- toolGetMappingCoord2Country()
   cellnames    <- paste(coordMapping$coords, coordMapping$iso, sep = ".")
   x <- new.magpie(cells_and_regions = cellnames,
                   years = seq(1995, 2150, 5),
@@ -24,7 +24,7 @@ calcDegradationYieldReduction <- function(cells = "lpjcell") {
                   fill = 0)
 
   if (cells == "magpiecell") {
-    x <- mrcommons::toolCoord2Isocell(x, cells = cells)
+    x <- toolCoord2Isocell(x, cells = cells)
   }
 
   return(list(x = x,

R/calcEFRRockstroem.R

@@ -13,7 +13,8 @@
 #' @import magclass
 #' @import madrat
 #' @importFrom stats quantile
-#' @importFrom mrcommons toolHarmonize2Baseline toolLPJmLVersion
+#' @importFrom mstools toolHarmonize2Baseline
+#' @importFrom mrlandcore toolLPJmLVersion
 #'
 #' @return magpie object in cellular resolution
 #' @author Felicitas Beier, Jens Heinke

R/calcEFRSmakthin.R

@@ -22,7 +22,8 @@
 #' @import magclass
 #' @import madrat
 #' @importFrom stats quantile
-#' @importFrom mrcommons toolHarmonize2Baseline toolLPJmLVersion
+#' @importFrom mstools toolHarmonize2Baseline
+#' @importFrom mrlandcore toolLPJmLVersion
 #'
 #' @return magpie object in cellular resolution
 #' @author Felicitas Beier, Abhijeet Mishra

R/calcEnvmtlFlow.R

@@ -11,7 +11,8 @@
 #' @import magclass
 #' @import madrat
 #' @importFrom stats quantile
-#' @importFrom mrcommons toolHarmonize2Baseline toolLPJmLVersion
+#' @importFrom mstools toolHarmonize2Baseline
+#' @importFrom mrlandcore toolLPJmLVersion
 #'
 #' @return magpie object in cellular resolution
 #' @author Felicitas Beier

R/calcGrasslandBiomass.R

@@ -1,5 +1,6 @@
 #' @title calcGrasslandBiomass
-#' @description Calculates pasture biomass demand for the historical period split between rangelands and managed pastures.
+#' @description Calculates pasture biomass demand for the historical period split
+#' between rangelands andmanaged pastures.
 #' @param cells "magpiecell" for 59199 cells or "lpjcell" for 67420 cells
 #' @return Regional biomass demand
 #' @author Marcos Alves
@@ -9,11 +10,10 @@
 #' \dontrun{
 #' calcOutput("GrasslandBiomass")
 #' }
-#' @importFrom mrcommons toolCoord2Isocell
+#' @importFrom mstools toolCoord2Isocell
 #' @importFrom magpiesets findset
 
 calcGrasslandBiomass <- function(cells = "lpjcell") {
-
   # select years
   magYearsPast <- findset("past")
 
@@ -33,17 +33,11 @@ calcGrasslandBiomass <- function(cells = "lpjcell") {
   # "other land" that is assumed to be used for grazing in those three countries.
 
   grasslLand["IND", , "pastr"] <- grasslLand["IND", , "pastr"] +
-                                    setNames(dimSums(land["IND", , c("primother", "secdother")],
-                                                    dim = 3),
-                                             "pastr")
+    setNames(dimSums(land["IND", , c("primother", "secdother")], dim = 3), "pastr")
   grasslLand["BGD", , "pastr"] <- grasslLand["BGD", , "pastr"] +
-                                    setNames(dimSums(land["BGD", , c("primother", "secdother")],
-                                                     dim = 3),
-                                              "pastr")
+    setNames(dimSums(land["BGD", , c("primother", "secdother")], dim = 3), "pastr")
   grasslLand["PAK", , "pastr"] <- grasslLand["PAK", , "pastr"] +
-                                    setNames(dimSums(land["PAK", , c("primother", "secdother")],
-                                                     dim = 3),
-                                              "pastr")
+    setNames(dimSums(land["PAK", , c("primother", "secdother")], dim = 3), "pastr")
 
   grassYld <- calcOutput("GrasslandsYields",
                          lpjml = "lpjml5p2_pasture",
@@ -66,7 +60,7 @@ calcGrasslandBiomass <- function(cells = "lpjcell") {
   livestock <- setNames(readSource("GLW3", subtype = "Aw"),
                         "liv_numb")
   if (cells == "magpiecell") {
-       livestock <- toolCoord2Isocell(livestock)
+    livestock <- toolCoord2Isocell(livestock)
   }
   livestock[livestock < 1] <- 0
 
@@ -80,11 +74,11 @@ calcGrasslandBiomass <- function(cells = "lpjcell") {
   livstSplit <- livestock * potBioMassShare
   livstSplit <- collapseNames(livstSplit)
   if (cells == "lpjcell") {
-       livstSplitCtry <- dimSums(livstSplit, dim = c("x", "y"))
+    livstSplitCtry <- dimSums(livstSplit, dim = c("x", "y"))
   } else if (cells == "magpiecell") {
-       livstSplitCtry <- dimSums(livstSplit, dim = 1.2)
+    livstSplitCtry <- dimSums(livstSplit, dim = 1.2)
   } else {
-       stop("Please select cells argument in calcGrasslandBiomass")
+    stop("Please select cells argument in calcGrasslandBiomass")
   }
   livstShareCtry <- livstSplitCtry[, , "pastr"] / dimSums(livstSplitCtry, dim = 3)
   livstShareCtry[is.nan(livstShareCtry) | is.infinite(livstShareCtry)] <- 0
@@ -96,7 +90,7 @@ calcGrasslandBiomass <- function(cells = "lpjcell") {
   # with the production of grass in pastures and rangelands in a country. That can be
   # derived by the fact that the feedbaskets assume the same feed ingredients shares
   # within a country.
-  commonCtrs <- intersect(getItems(biomass, dim = 1), 
+  commonCtrs <- intersect(getItems(biomass, dim = 1),
                           unique(getItems(livstShareCtry, dim = 1)))
   biomassSplit <- biomass[commonCtrs, , ] * livstShareCtry[commonCtrs, , ]
   biomassSplit <- toolCountryFill(biomassSplit, fill = 0)

R/calcIrrigation.R

@@ -18,7 +18,8 @@
 #' }
 #'
 #' @importFrom magpiesets findset
-#' @importFrom mrcommons toolLPJmLVersion toolGetMappingCoord2Country toolCoord2Isocell
+#' @importFrom mrlandcore toolLPJmLVersion
+#' @importFrom mstools toolGetMappingCoord2Country toolCoord2Isocell
 #' @importFrom madrat toolGetMapping calcOutput toolAggregate
 #' @importFrom magclass dimSums getItems getSets collapseNames
 #' @importFrom withr local_options
@@ -59,16 +60,16 @@ calcIrrigation <- function(lpjml = c(natveg = "LPJmL4_for_MAgPIE_44ac93de", crop
 
   # Clustering weight:
   totalCropland <- dimSums(calcOutput("Croparea", sectoral = "kcr", physical = TRUE,
-                                       cellular = TRUE, cells = "lpjcell",
-                                       years = "y1995", round = 6,
-                                       irrigation = TRUE, aggregate = FALSE),
-                            dim = 3.2)
+                                      cellular = TRUE, cells = "lpjcell",
+                                      years = "y1995", round = 6,
+                                      irrigation = TRUE, aggregate = FALSE),
+                           dim = 3.2)
   map <- toolGetMappingCoord2Country()
   getItems(totalCropland, dim = 1, raw = TRUE) <- paste(map$coords, map$iso, sep = ".")
   getSets(totalCropland) <- c("x", "y", "iso", "year", "irrigation")
 
   weightCropArea <- collapseNames(totalCropland[, , "irrigated"]) +
-                                  rainfedweight * collapseNames(totalCropland[, , "rainfed"])
+    rainfedweight * collapseNames(totalCropland[, , "rainfed"])
 
   # Reduce to 59199 cells
   if (cells == "magpiecell") {