IPCC climate class source + enable calcClimateClass to process it

.buildlibrary

@@ -1,4 +1,4 @@
-ValidationKey: '5209960'
+ValidationKey: '5396320'
 AcceptedWarnings:
 - 'Warning: package ''.*'' was built under R version'
 - 'Warning: namespace ''.*'' is not available and has been replaced'

.zenodo.json

@@ -1,6 +1,6 @@
 {
   "title": "mrmagpie: madrat based MAgPIE Input Data Library",
-  "version": "0.28.0",
+  "version": "0.29.0",
   "description": "<p>Provides functions for MAgPIE country and cellular input data generation.<\/p>",
   "creators": [
     {

DESCRIPTION

@@ -1,8 +1,8 @@
 Package: mrmagpie
 Type: Package
 Title: madrat based MAgPIE Input Data Library
-Version: 0.28.0
-Date: 2020-12-11
+Version: 0.29.0
+Date: 2020-12-12
 Authors@R: c(person("Kristine", "Karstens", email = "[email protected]", role = c("aut","cre")),
              person("Jan Philipp", "Dietrich", email = "[email protected]", role = "aut"),
              person("David", "Chen", role = "aut"),

NAMESPACE

@@ -78,6 +78,7 @@ importFrom(raster,area)
 importFrom(raster,as.matrix)
 importFrom(raster,brick)
 importFrom(raster,extent)
+importFrom(raster,extract)
 importFrom(raster,projectRaster)
 importFrom(raster,raster)
 importFrom(raster,rasterToPoints)
@@ -91,5 +92,7 @@ importFrom(stats,kmeans)
 importFrom(stats,quantile)
 importFrom(tidyr,pivot_wider)
 importFrom(tools,file_ext)
+importFrom(utils,download.file)
 importFrom(utils,read.table)
+importFrom(utils,unzip)
 importFrom(utils,write.table)

R/calcClimateClass.R

@@ -1,5 +1,6 @@
 #' @title calcClimateClass
 #' @description fraction of a cell belonging to a given climate classification based on Koeppen Geiger Classification. http://koeppen-geiger.vu-wien.ac.at/.
+#' @param source select source from: Koeppen, IPCC, IPCC_reduced
 #'
 #' @return Clustered MAgPIE object on requested resolution
 #' @author Abhijeet Mishra
@@ -9,9 +10,24 @@
 #'
 #' @export
 
-calcClimateClass <-function(){
+calcClimateClass <-function(source="Koeppen"){
+
+  if(source=="Koeppen"){
+
+    x      <- readSource("Koeppen", subtype="cellular",convert = "onlycorrect")
+
+  } else if(grepl("IPCC",source)){
+
+    x <- readSource("IPCCClimate", convert="onlycorrect")
+    getNames(x) <- gsub(" ","_", tolower(getNames(x)))
+
+    if(source=="IPCC_reduced"){
+      reduceIPCC  <- toolGetMapping("IPCC2IPCCreduced.csv", type = "sectoral")
+      x           <- toolAggregate(x,reduceIPCC,from="ipcc",to="ipcc_reduced", dim=3, partrel=TRUE)
+    }
+
+  } else { stop("Source unkown.")}
 
-  x      <- readSource("Koeppen", subtype="cellular",convert = FALSE)
   weight <- dimSums(calcOutput("LanduseInitialisation", aggregate=FALSE, cellular=TRUE, land="fao", input_magpie=TRUE, years="y1995", round=6), dim=3)
 
   return(list(

R/correctIPCCClimate.R

@@ -0,0 +1,30 @@
+#' @title correctIPCCClimate
+#' @description Correct IPCC climate classification
+#'
+#' @return Magpie object with results on cellular level for 12 IPCC climate zone types
+#' @param x magpie object provided by the read function
+#' @author  Kristine Karstens
+#' @examples
+#'
+#' \dontrun{
+#' readSource("IPCCClimate", convert="onlycorrect")
+#' }
+
+correctIPCCClimate <-  function(x){
+
+  ### determine gaps on iso level
+  iso <- unique(substring(where(setYears(x[,,"NA"], "y2010")==1)$true$reg,1,3))
+
+  ## move unknown cells to most common country values
+  nmax        <- rep(0,length(iso))
+  names(nmax) <- iso
+  for(i in iso){
+    nmax[i] <- which.max(dimSums((x[i,,]), dim=1))
+    x[i,,nmax[i]] <- x[i,,nmax[i]] + x[i,,"NA"]
+  }
+
+  if(any(x[,,"NA"]==1)) vcat(2,"Still grid cells without climate zone")
+  out <- x[,,"NA",invert=TRUE]
+
+  return(out)
+}

R/downloadIPCCClimate.R

@@ -0,0 +1,34 @@
+#' @title downloadIPCCClimate
+#' @description Download IPCC climate classification
+#'
+#' @return Meta information on downloaded data
+#' @author  Kristine Karstens
+#' @examples
+#'
+#' \dontrun{
+#' readSource("IPCCClimate", convert="onlycorrect")
+#' }
+#'
+#' @importFrom utils download.file unzip
+
+downloadIPCCClimate <- function() {
+
+  # Define meta data
+  meta <-  list(title = "Thematic Data Layers for Commission Decision of [10 June 2010] on guidelines for the calculation of land carbon stocks for the purpose of Annex V to Directive 2009/28/EC",
+                url   = "https://esdac.jrc.ec.europa.eu/projects/RenewableEnergy/Data/Climate_Zone.zip")
+
+  download.file(meta$url, destfile = "ipccclimate.zip")
+  unzip("ipccclimate.zip")
+  unlink("ipccclimate.zip")
+
+  # Compose meta data by adding elements that are the same for all subtypes.
+  return(list(url           = meta$url,
+              doi           = NULL,
+              title         = meta$title,
+              author        = NULL,
+              version       = NULL,
+              release_date  = NULL,
+              license       = NULL,
+              reference     = NULL)
+  )
+}

R/readIPCCClimate.R

@@ -0,0 +1,36 @@
+#' @title readIPCCClimate
+#' @description Read IPCC climate classification
+#'
+#' @return Magpie object with results on cellular level for 12 IPCC climate zone types
+#' @author  Kristine Karstens
+#' @examples
+#'
+#' \dontrun{
+#' readSource("IPCCClimate", convert="onlycorrect")
+#' }
+#'
+#' @importFrom raster raster aggregate extract
+
+readIPCCClimate <-  function(){
+
+  raster_1d12   <- raster("CLIMATE_ZONE.rst")
+  zone_names    <- as.character(levels(raster_1d12)[[1]]$Class_name)
+  raster_1d2    <- aggregate(raster_1d12, fact=6, fun=max) # to avoid gaps (since 0 is NA)
+
+  map           <- as.data.frame(magpie_coord)
+  mag           <- clean_magpie(as.magpie(extract(raster_1d2,map), spatial=1))
+  #map[mag==0]   <- 6
+  cellNames     <- toolMappingFile(type="cell",name="CountryToCellMapping.csv",readcsv=TRUE)$celliso
+  getNames(mag) <- "NA"
+  getYears(mag) <- NULL
+  getCells(mag) <- cellNames
+  getSets(mag)    <- c("country.cell","t","climatezone")
+
+  out   <- add_columns(mag, dim=3.1, addnm=zone_names)
+  out[] <- 0
+  for(zone in c(zone_names)){out[,,zone][which(mag==which(zone_names==zone))] <- 1}
+  out[,,"NA"][which(dimSums(out, dim=3)==0)] <- 1
+  out <- mbind(out[,,zone_names],out[,,"NA"])
+
+  return(out)
+}

README.md

@@ -1,6 +1,6 @@
 # madrat based MAgPIE Input Data Library
 
-R package **mrmagpie**, version **0.28.0**
+R package **mrmagpie**, version **0.29.0**
 
 
 
@@ -38,9 +38,8 @@ In case of questions / problems please contact Kristine Karstens <karstens@pik-p
 
 To cite package **mrmagpie** in publications use:
 
-Karstens K, Dietrich J, Chen D, Windisch M, Alves M, Beier F, v.
-Jeetze P, Mishra A, Humpenoeder F (2020). _mrmagpie: madrat
-based MAgPIE Input Data Library_. R package version 0.28.0.
+Karstens K, Dietrich J, Chen D, Windisch M, Alves M, Beier F, v. Jeetze P, Mishra A, Humpenoeder F (2020). _mrmagpie: madrat
+based MAgPIE Input Data Library_. R package version 0.29.0.
 
 A BibTeX entry for LaTeX users is
 
@@ -49,7 +48,7 @@ A BibTeX entry for LaTeX users is
   title = {mrmagpie: madrat based MAgPIE Input Data Library},
   author = {Kristine Karstens and Jan Philipp Dietrich and David Chen and Michael Windisch and Marcos Alves and Felicitas Beier and Patrick {v. Jeetze} and Abhijeet Mishra and Florian Humpenoeder},
   year = {2020},
-  note = {R package version 0.28.0},
+  note = {R package version 0.29.0},
 }
 ```