Merge pull request #133 from fbenke-pik/gdp

replace unit conversion functions with madrat tool wrappers
pik-piam · Oct 11, 2024 · b8e5d6e · b8e5d6e
2 parents 3ec2e7b + 32fde78
commit b8e5d6e
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diff --git a/.buildlibrary b/.buildlibrary
@@ -1,11 +1,12 @@
-ValidationKey: '288340884'
+ValidationKey: '288360891'
 AcceptedWarnings:
 - 'Warning: package ''.*'' was built under R version'
 - 'Warning: namespace ''.*'' is not available and has been replaced'
 AcceptedNotes:
 - unable to verify current time
 - Imports includes .* non-default packages.
 - installed size is .*
+- .* includes the non-default packages.*
 AutocreateReadme: yes
 allowLinterWarnings: no
 enforceVersionUpdate: no
diff --git a/CITATION.cff b/CITATION.cff
@@ -2,7 +2,7 @@ cff-version: 1.2.0
 message: If you use this software, please cite it using the metadata from this file.
 type: software
 title: 'mrcommons: MadRat commons Input Data Library'
-version: 1.44.12
+version: 1.44.13
 date-released: '2024-10-11'
 abstract: Provides useful functions and a common structure to all the input data required
   to run models like MAgPIE and REMIND of model input data.

diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,7 +1,7 @@
 Package: mrcommons
 Type: Package
 Title: MadRat commons Input Data Library
-Version: 1.44.12
+Version: 1.44.13
 Date: 2024-10-11
 Authors@R: c(person("Benjamin Leon", "Bodirsky", email = "bodirsky@pik-potsdam.de", role = "aut"),
              person("Kristine", "Karstens", role = "aut"),
@@ -40,6 +40,7 @@ Description: Provides useful functions and a common structure to all the input d
     and REMIND of model input data.
 Depends:
     R (>= 2.10.0),
+    GDPuc (>= 1.3.0),
     magclass (>= 3.17),
     madrat (>= 3.10.0),
     mrdrivers (>= 1.0.0),
@@ -50,7 +51,6 @@ Imports:
     data.table,
     dplyr,
     hdf5r,
-    GDPuc (>= 1.0.5),
     luscale,
     magpiesets (>= 0.44.2),
     ncdf4,

diff --git a/NAMESPACE b/NAMESPACE
@@ -28,13 +28,14 @@ export(readHoulton2018)
 export(readJRC_IDEES)
 export(toolCalcIEAfromStructureMappingPEFE)
 export(toolPregnant)
+import(GDPuc)
 import(madrat)
 import(magclass)
 import(mrdrivers)
 import(mrfaocore)
 import(mrlandcore)
 import(mstools)
-importFrom(GDPuc,convertGDP)
+importFrom(GDPuc,toolConvertGDP)
 importFrom(countrycode,countrycode)
 importFrom(data.table,":=")
 importFrom(data.table,as.data.table)

diff --git a/R/calcGTAPTotalTransportCosts.R b/R/calcGTAPTotalTransportCosts.R
@@ -46,9 +46,9 @@ calcGTAPTotalTransportCosts <- function(costType = "transport", version = "9") {
   # half of transport of inputs to market and half of transport from market to consumer
   totalTcosts <- (tcostInputs + tcostToSecondary) / 2
 
-  totalTcosts <-  GDPuc::convertGDP(totalTcosts, unit_in = "current US$MER",
-                                    unit_out = "constant 2017 US$MER",
-                                    replace_NAs = "no_conversion")
+  totalTcosts <-  GDPuc::toolConvertGDP(totalTcosts, unit_in = "current US$MER",
+                                        unit_out = "constant 2017 US$MER",
+                                        replace_NAs = "no_conversion")
 
   return(list(x = totalTcosts,
               weight = NULL,

diff --git a/R/calcIniFoodPrice.R b/R/calcIniFoodPrice.R
@@ -75,9 +75,9 @@ calcIniFoodPrice <- function(datasource = "FAO", year = "y2005", products = "kfo
               "brans", "distillers_grain", "ethanol", "fibres", "molasses", "wood", "woodfuel", "begr",
               "betr", "res_cereals", "res_fibrous", "pasture", "scp")
     getItems(out, dim = 1) <- "USA"
-    out[, , conv] <- GDPuc::convertGDP(out[, , conv], unit_in = "constant 2005 US$MER",
-                                       unit_out = "constant 2017 US$MER",
-                                       replace_NAs = "no_conversion")
+    out[, , conv] <- GDPuc::toolConvertGDP(out[, , conv], unit_in = "constant 2005 US$MER",
+                                           unit_out = "constant 2017 US$MER",
+                                           replace_NAs = "no_conversion")
     getItems(out, dim = 1) <- "GLO"
 
     # correct the prices for dry matter values
@@ -122,9 +122,9 @@ calcIniFoodPrice <- function(datasource = "FAO", year = "y2005", products = "kfo
               "betr", "res_cereals", "res_fibrous", "pasture", "scp",
               "foddr", "sugar")
     getItems(out, dim = 1) <- "USA"
-    out[, , conv] <- GDPuc::convertGDP(out[, , conv], unit_in = "constant 2005 US$MER",
-                                       unit_out = "constant 2017 US$MER",
-                                       replace_NAs = "no_conversion")
+    out[, , conv] <- GDPuc::toolConvertGDP(out[, , conv], unit_in = "constant 2005 US$MER",
+                                           unit_out = "constant 2017 US$MER",
+                                           replace_NAs = "no_conversion")
     getItems(out, dim = 1) <- "GLO"
 
     # correct the prices from online sources for dry matter values

diff --git a/R/calcMAgPIEReport.R b/R/calcMAgPIEReport.R
@@ -7,7 +7,7 @@ calcMAgPIEReport <- function(subtype) {
     # with transformation factor from 10E6 US$2005 to 10E12 US$2005
     x <- x[, , "Costs Without Incentives (million US$05/yr)"] / 1000 / 1000
     # convert from US$2005 -> US$2017
-    x <- GDPuc::convertGDP(
+    x <- GDPuc::toolConvertGDP(
       gdp = x,
       unit_in = "constant 2005 US$MER",
       unit_out = "constant 2017 Int$PPP",
@@ -20,7 +20,7 @@ calcMAgPIEReport <- function(subtype) {
     # with transformation factor from 10E6 US$2005 to 10E12 US$2005
     x <- x[, , "Costs Accounting|+|MACCS (million US$05/yr)"] / 1000 / 1000
     # convert from US$2005 -> US$2017
-    x <- GDPuc::convertGDP(
+    x <- GDPuc::toolConvertGDP(
       gdp = x,
       unit_in = "constant 2005 US$MER",
       unit_out = "constant 2017 Int$PPP",

diff --git a/R/calcPriceAgriculture.R b/R/calcPriceAgriculture.R
@@ -186,10 +186,10 @@ calcPriceAgriculture <- function(datasource = "IMPACT3.2.2World_Price", unit = "
 
   if (unit != "US$17/tDM") {
     # Transform to selected currency unit
-    out <- GDPuc::convertGDP(out,
-                             unit_in = "constant 2017 US$MER",
-                             unit_out =  unit,
-                             replace_NAs = "no_conversion")
+    out <- GDPuc::toolConvertGDP(out,
+                                 unit_in = "constant 2017 US$MER",
+                                 unit_out =  unit,
+                                 replace_NAs = "no_conversion")
   }
 
   if (!is.null(weight)) {

diff --git a/R/calcWBGEM.R b/R/calcWBGEM.R
@@ -47,9 +47,9 @@ calcWBGEM <- function() {
 
   # inflate to 2017 using US inflation for global value
   getItems(out, dim = 1) <- "USA"
-  out <- GDPuc::convertGDP(out, unit_in = "constant 2005 US$MER",
-                           unit_out = "constant 2017 US$MER",
-                           replace_NAs = "no_conversion")
+  out <- GDPuc::toolConvertGDP(out, unit_in = "constant 2005 US$MER",
+                               unit_out = "constant 2017 US$MER",
+                               replace_NAs = "no_conversion")
   getItems(out, dim = 1) <- "GLO"
 
   return(list(x = out,

diff --git a/R/convertGTAPv8v9.R b/R/convertGTAPv8v9.R
@@ -8,7 +8,7 @@
 #' \dontrun{
 #' a <- readSource("convertGTAPv8v9", "81:SF01", convert = TRUE)
 #' }
-#' @importFrom GDPuc convertGDP
+#' @importFrom GDPuc toolConvertGDP
 convertGTAPv8v9 <- function(x, subtype) {
 
   split <- toolSplitSubtype(subtype, list(version = NULL, header = NULL))
@@ -68,10 +68,10 @@ convertGTAPv8v9 <- function(x, subtype) {
     gdpMer <- calcOutput("GDPPast", GDPPast = "WDI-MI",
                          unit = "constant 2017 US$MER", aggregate = FALSE)
     gdpMer <- gdpMer[, getYears(x), , drop = TRUE]
-    w1 <- GDPuc::convertGDP(gdpMer,
-                            unit_in = "constant 2017 US$MER",
-                            unit_out = "current US$MER",
-                            replace_NAs = "no_conversion")
+    w1 <- GDPuc::toolConvertGDP(gdpMer,
+                                unit_in = "constant 2017 US$MER",
+                                unit_out = "current US$MER",
+                                replace_NAs = "no_conversion")
     getNames(w1) <- NULL
     w2 <- w1
 

diff --git a/R/convertICP2017.R b/R/convertICP2017.R
@@ -17,9 +17,9 @@ convertICP2017 <- function(x, subtype = "per_cap_expMER") {
   # currency convert for expenditures
   if (subtype == "per_cap_expMER") {
 
-    x2011 <- GDPuc::convertGDP(x[, 2011, ],
-                               unit_in = "constant 2011 US$MER",
-                               unit_out = "constant 2017 US$MER")
+    x2011 <- GDPuc::toolConvertGDP(x[, 2011, ],
+                                   unit_in = "constant 2011 US$MER",
+                                   unit_out = "constant 2017 US$MER")
     x2017 <- x[, 2017, ]
     x <- mbind(x2011, x2017)
     x[is.na(x)] <- 0
@@ -28,9 +28,9 @@ convertICP2017 <- function(x, subtype = "per_cap_expMER") {
   # currency convert for expenditures
   if (subtype == "per_cap_expPPP") {
 
-    x2011 <- GDPuc::convertGDP(x[, 2011, ],
-                               unit_in = "constant 2011 US$PPP",
-                               unit_out = "constant 2017 US$MER")
+    x2011 <- GDPuc::toolConvertGDP(x[, 2011, ],
+                                   unit_in = "constant 2011 US$PPP",
+                                   unit_out = "constant 2017 US$MER")
     x2017 <- x[, 2017, ]
     x <- mbind(x2011, x2017)
     x[is.na(x)] <- 0

diff --git a/R/convertSSPResults.R b/R/convertSSPResults.R
@@ -94,8 +94,8 @@ convertSSPResults <- function(x) {
   data <- x[, , selection]
   data[is.na(data)] <- 0
   #convert from USD05MER to USD17MER based on USA values for all countries as the CO2 price is global.
-  data <- data * round(GDPuc::convertSingle(1, "USA", unit_in = "constant 2005 US$MER",
-                                            unit_out = "constant 2017 US$MER"), 2)
+  data <- data * round(GDPuc::toolConvertSingle(1, "USA", unit_in = "constant 2005 US$MER",
+                                                unit_out = "constant 2017 US$MER"), 2)
   getNames(data, dim = 3) <- "Price|Carbon (US$2017/t CO2)"
   aggregatedREG <- toolAggregate(data, rel = mappingFile, weight = NULL, dim = 1, partrel = TRUE,
                                  from = "RegionCode", to = "CountryCode")
@@ -107,9 +107,9 @@ convertSSPResults <- function(x) {
   selection <- c("Price|Primary Energy|Biomass (US$2005/GJ)")
 
   data <- x[, , selection]
-  data <- convertGDP(data, unit_in = "constant 2005 US$MER",
-                     unit_out = "constant 2017 US$MER",
-                     replace_NAs = "no_conversion")
+  data <- toolConvertGDP(data, unit_in = "constant 2005 US$MER",
+                         unit_out = "constant 2017 US$MER",
+                         replace_NAs = "no_conversion")
   getNames(data, dim = 3) <- "Price|Primary Energy|Biomass (US$2017/GJ)"
   aggregatedREG <- toolAggregate(data, rel = mappingFile, weight = NULL, dim = 1, partrel = TRUE,
                                  from = "RegionCode", to = "CountryCode")

diff --git a/R/imports.R b/R/imports.R
@@ -1,4 +1,4 @@
 # Generated by lucode2: do not edit by hand
 
-#' @import magclass madrat mrdrivers mrfaocore mrlandcore mstools
+#' @import GDPuc magclass madrat mrdrivers mrfaocore mrlandcore mstools
 NULL
diff --git a/R/readIMPACT3.2.2World_Price.R b/R/readIMPACT3.2.2World_Price.R
@@ -22,10 +22,10 @@ readIMPACT3.2.2World_Price <- function() { # nolint: object_name_linter.
 
   #inflate to 2017 using US inflation for global value
   getItems(data, dim = 1) <- "USA"
-  data <- GDPuc::convertGDP(data,
-                            unit_in = "constant 2005 US$MER",
-                            unit_out = "constant 2017 US$MER",
-                            replace_NAs = "no_conversion")
+  data <- GDPuc::toolConvertGDP(data,
+                                unit_in = "constant 2005 US$MER",
+                                unit_out = "constant 2017 US$MER",
+                                replace_NAs = "no_conversion")
   getItems(data, dim = 1) <- "GLO"
 
   return(data)

diff --git a/README.md b/README.md
@@ -1,6 +1,6 @@
 # MadRat commons Input Data Library
 
-R package **mrcommons**, version **1.44.12**
+R package **mrcommons**, version **1.44.13**
 
 [![CRAN status](https://www.r-pkg.org/badges/version/mrcommons)](https://cran.r-project.org/package=mrcommons) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3822009.svg)](https://doi.org/10.5281/zenodo.3822009) [![R build status](https://github.com/pik-piam/mrcommons/workflows/check/badge.svg)](https://github.com/pik-piam/mrcommons/actions) [![codecov](https://codecov.io/gh/pik-piam/mrcommons/branch/master/graph/badge.svg)](https://app.codecov.io/gh/pik-piam/mrcommons) [![r-universe](https://pik-piam.r-universe.dev/badges/mrcommons)](https://pik-piam.r-universe.dev/builds)
 
@@ -39,7 +39,7 @@ In case of questions / problems please contact Jan Philipp Dietrich <dietrich@pi
 
 To cite package **mrcommons** in publications use:
 
-Bodirsky B, Karstens K, Baumstark L, Weindl I, Wang X, Mishra A, Wirth S, Stevanovic M, Steinmetz N, Kreidenweis U, Rodrigues R, Popov R, Humpenoeder F, Giannousakis A, Levesque A, Klein D, Araujo E, Beier F, Oeser J, Pehl M, Leip D, Crawford M, Molina Bacca E, von Jeetze P, Martinelli E, Schreyer F, Soergel B, Sauer P, Hötten D, Hasse R, Abrahão G, Weigmann P, Dietrich J (2024). _mrcommons: MadRat commons Input Data Library_. doi:10.5281/zenodo.3822009 <https://doi.org/10.5281/zenodo.3822009>, R package version 1.44.12, <https://github.com/pik-piam/mrcommons>.
+Bodirsky B, Karstens K, Baumstark L, Weindl I, Wang X, Mishra A, Wirth S, Stevanovic M, Steinmetz N, Kreidenweis U, Rodrigues R, Popov R, Humpenoeder F, Giannousakis A, Levesque A, Klein D, Araujo E, Beier F, Oeser J, Pehl M, Leip D, Crawford M, Molina Bacca E, von Jeetze P, Martinelli E, Schreyer F, Soergel B, Sauer P, Hötten D, Hasse R, Abrahão G, Weigmann P, Dietrich J (2024). _mrcommons: MadRat commons Input Data Library_. doi:10.5281/zenodo.3822009 <https://doi.org/10.5281/zenodo.3822009>, R package version 1.44.13, <https://github.com/pik-piam/mrcommons>.
 
 A BibTeX entry for LaTeX users is
 
@@ -48,8 +48,8 @@ A BibTeX entry for LaTeX users is
   title = {mrcommons: MadRat commons Input Data Library},
   author = {Benjamin Leon Bodirsky and Kristine Karstens and Lavinia Baumstark and Isabelle Weindl and Xiaoxi Wang and Abhijeet Mishra and Stephen Wirth and Mishko Stevanovic and Nele Steinmetz and Ulrich Kreidenweis and Renato Rodrigues and Roman Popov and Florian Humpenoeder and Anastasis Giannousakis and Antoine Levesque and David Klein and Ewerton Araujo and Felicitas Beier and Julian Oeser and Michaja Pehl and Debbora Leip and Michael Crawford and Edna {Molina Bacca} and Patrick {von Jeetze} and Eleonora Martinelli and Felix Schreyer and Bjoern Soergel and Pascal Sauer and David Hötten and Robin Hasse and Gabriel Abrahão and Pascal Weigmann and Jan Philipp Dietrich},
   year = {2024},
-  note = {R package version 1.44.12},
-  doi = {10.5281/zenodo.3822009},
+  note = {R package version 1.44.13},
   url = {https://github.com/pik-piam/mrcommons},
+  doi = {10.5281/zenodo.3822009},
 }
 ```