remove documentation warnings and cleanup DESCRIPTION

.buildlibrary

@@ -1,4 +1,4 @@
-ValidationKey: '34678800'
+ValidationKey: '34700316'
 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: 'mrremind: MadRat REMIND Input Data Package'
-version: 0.175.5
-date-released: '2024-02-07'
+version: 0.175.6
+date-released: '2024-02-08'
 abstract: The mrremind packages contains data preprocessing for the REMIND model.
 authors:
 - family-names: Baumstark

DESCRIPTION

@@ -1,8 +1,8 @@
 Type: Package
 Package: mrremind
 Title: MadRat REMIND Input Data Package
-Version: 0.175.5
-Date: 2024-02-07
+Version: 0.175.6
+Date: 2024-02-08
 Authors@R: c(
     person("Lavinia", "Baumstark", , "[email protected]", role = c("aut", "cre")),
     person("Renato", "Rodrigues", role = "aut"),
@@ -37,12 +37,12 @@ Description: The mrremind packages contains data preprocessing for the
 License: LGPL-3 | file LICENSE
 URL: https://github.com/pik-piam/mrremind
 Depends:
-    R (>= 2.10.0),
+    edgeTransport (>= 0.17.0),
     madrat (>= 3.7.1),
     magclass (>= 6.11.3),
-    mrdrivers (>= 1.0.0),
     mrcommons (>= 1.38.0),
-    edgeTransport (>= 0.17.0)
+    mrdrivers (>= 1.0.0),
+    R (>= 2.10.0)
 Imports:
     assertr,
     assertthat,
@@ -60,18 +60,18 @@ Imports:
     plyr,
     purrr,
     quitte (>= 0.3105.0),
+    R.utils,
     readODS,
     readr,
     readxl,
     reshape,
     reshape2,
     rlang,
     rmndt,
-    R.utils,
     tibble,
     tidyr,
     tidyselect,
-    zoo,
+    zoo
 Suggests: 
     covr,
     knitr,
@@ -82,4 +82,3 @@ VignetteBuilder:
 Encoding: UTF-8
 LazyData: no
 RoxygenNote: 7.3.1
-

R/calcTheil.R

@@ -1,88 +1,101 @@
 #' Calculate regional Theil-T index
 #'
 
-#' To calculate the regional Theil-T index (= correction to welfare function for a lognormal income distribution) we do the following:
-#' (1) convert country-level Gini coefficients to Theil (2) calculate contribution to Theil-T index that includes both between-countries and within-country inequality
-#' (see e.g. https://en.wikipedia.org/wiki/Theil_index). The latter can then be aggregated with calcOutput().
+#' To calculate the regional Theil-T index (= correction to welfare function for
+#' a lognormal income distribution) we do the following:
+#' (1) convert country-level Gini coefficients to Theil (2) calculate contribution
+#' to Theil-T index that includes both between-countries and within-country inequality
+#' (see e.g. https://en.wikipedia.org/wiki/Theil_index). The latter can then be
+#' aggregated with calcOutput().
 #'
-#' NB 1: the aggregation depends on the region mapping. It is implemented such that the regionmapping specified in getConfig()$regionmapping is used.
+#' NB 1: the aggregation depends on the region mapping. It is implemented such
+#' that the regionmapping specified in getConfig()$regionmapping is used.
 #'
-#' NB 2: the result of calcOutput('Theil', aggregate = FALSE), is NOT the country Theil-T, but the unweighted contribution from a given country to the regional value.
+#' NB 2: the result of calcOutput('Theil', aggregate = FALSE), is NOT the country
+#' Theil-T, but the unweighted contribution from a given country to the regional value.
 #'
-#' @return magpie objects of unweighted contribution to Theil, weights (= country shares of regional GDP), docstring
+#' @return magpie objects of unweighted contribution to Theil,
+#' weights (= country shares of regional GDP), docstring
 #' @author Bjoern Soergel
 #' @seealso \code{\link{calcOutput}} \code{\link{convertGini},\link{readGini}}
 #' @examples
-#'
-#' \dontrun{ a <- calcOutput("Theil")
+#' \dontrun{
+#' a <- calcOutput("Theil")
 #' }
 #'
 #' @importFrom stats qnorm
 
-calcTheil <- function(){
-  #Gini & Theil
-  Gini <- readSource('Gini')
+calcTheil <- function() {
+
+  ##  helper functions.
+  TheilT.from.sigma <- function(sigma) {
+    # Theil T coefficient for lognormal distribution
+    TheilT <- sigma^2 / 2.
+    return(TheilT)
+  }
+
+  sigma.from.Gini <- function(G) {
+    # assuming lognormal distribution: convert Gini to sigmas
+    sigma <- sqrt(2) * qnorm((G + 1) / 2)
+    return(sigma)
+  }
+
+  # Gini and Theil
+  Gini <- readSource("Gini")
   years <- getYears(Gini)
   TheilT <- TheilT.from.sigma(sigma.from.Gini(Gini))
 
   # population (in 1e6)
-  pop <- calcOutput(type = 'Population', aggregate = FALSE)
-  sspnames <- c(paste0('SSP',1:5),"SDP","SSP2EU")
-  pop <- pop[,years,paste0('pop_',sspnames)]
+  pop <- calcOutput(type = "Population", aggregate = FALSE)
+  sspnames <- c(paste0("SSP", 1:5), "SDP", "SSP2EU")
+  pop <- pop[, years, paste0("pop_", sspnames)]
   getNames(pop) <- sspnames
-  getSets(pop) <- c("iso3c","year","scenario")
+  getSets(pop) <- c("iso3c", "year", "scenario")
 
   # GDP (in million $ PPP 2005)
   GDPppp <- calcOutput(type = "GDP", aggregate = FALSE)
-  GDPnames <- paste0('gdp_',sspnames)
-  GDPppp <- GDPppp[,years,GDPnames]
+  GDPnames <- paste0("gdp_", sspnames)
+  GDPppp <- GDPppp[, years, GDPnames]
   getNames(GDPppp) <- sspnames
-  getSets(GDPppp) <- c("iso3c","year","scenario")
+  getSets(GDPppp) <- c("iso3c", "year", "scenario")
 
   # allocate empty objects for storing Theil contribution and weights
   contribTheilT <- pop
-  contribTheilT[,,] <- NA
+  contribTheilT[, , ] <- NA
   s_i <- pop
-  s_i[,,] <- NA
+  s_i[, , ] <- NA
 
   # contribution to Theil index depends on region mapping. We always use the one specified in getConfig().
-  regionmapping <- read.csv(toolGetMapping(type = 'regional', name = getConfig()$regionmapping, 
-                            returnPathOnly = TRUE, where = 'mappingfolder'),
-                            sep = ';', colClasses = 'character')
+  regionmapping <- read.csv(
+    toolGetMapping(
+      type = "regional", name = getConfig()$regionmapping,
+      returnPathOnly = TRUE, where = "mappingfolder"
+    ),
+    sep = ";", colClasses = "character"
+  )
+
   # GDP per capita
-  xbar_i <- GDPppp/pop
-  for (rr in unique(regionmapping$RegionCode)){
+  xbar_i <- GDPppp / pop
+  for (rr in unique(regionmapping$RegionCode)) {
     rrCountries <- regionmapping$CountryCode[regionmapping$RegionCode == rr]
     # regional GDP per capita
-    GDPppp_rr <- dimSums(GDPppp[rrCountries,,], dim = 1)
-    Ntot_rr <- dimSums(pop[rrCountries,,], dim = 1)
-    xbar_rr <- GDPppp_rr/Ntot_rr
+    GDPppp_rr <- dimSums(GDPppp[rrCountries, , ], dim = 1)
+    Ntot_rr <- dimSums(pop[rrCountries, , ], dim = 1)
+    xbar_rr <- GDPppp_rr / Ntot_rr
     # contribution to Theil index (unweighted)
-    contribTheilT[rrCountries,,] <- TheilT[rrCountries,,] + log(xbar_i[rrCountries,,]/xbar_rr)
+    contribTheilT[rrCountries, , ] <- TheilT[rrCountries, , ] + log(xbar_i[rrCountries, , ] / xbar_rr)
     # weights = income share of country i:
-    # s_i = N_i/N * xbar_i/xbar = GDP_i/GDP_rr
-    s_i[rrCountries,,] <- GDPppp[rrCountries,,]/GDPppp_rr
+    # s_i = N_i/N * xbar_i/xbar = GDP_i/GDP_rr # nolint
+    s_i[rrCountries, , ] <- GDPppp[rrCountries, , ] / GDPppp_rr
     # sanity check: ensure that weights for a region sum to one (within floating point precision)
-    assertthat::assert_that(max(abs(dimSums(s_i[rrCountries,,],dim=1) - 1)) < 1e-10)
+    assertthat::assert_that(max(abs(dimSums(s_i[rrCountries, , ], dim = 1) - 1)) < 1e-10)
   }
 
   # for easier REMIND integration use same names as GDP scenarios for Theil
   # change this if we later want to test effect of per capita income growth vs. inequality
   getNames(contribTheilT) <- GDPnames
   getNames(s_i) <- GDPnames
 
-  return(list(x = contribTheilT, weight = s_i, unit = "-", description = 'aggregated: Theil-T index, not-aggregated: unweighted contribution to Theil-T'))
-}
-
-##  helper functions.
-TheilT.from.sigma <- function(sigma){
-  # Theil T coefficient for lognormal distribution
-  TheilT <- sigma^2/2.
-  return(TheilT)
-}
-
-sigma.from.Gini <- function(G){
-  # assuming lognormal distribution: convert Gini to sigmas
-  sigma <- sqrt(2)*qnorm((G+1)/2)
-  return(sigma)
+  return(list(x = contribTheilT, weight = s_i, unit = "-",
+              description = "aggregated: Theil-T index, not-aggregated: unweighted contribution to Theil-T"))
 }

R/convertStrefler.R

@@ -1,10 +1,10 @@
 #' @title convertStrefler
 #' @description Converts data on enhanced weathering
 #' @param x unconverted magpie object from read-script
+#' @param subtype data subtype. Either "weathering_graderegi", or "weathering_costs"
 #'
 #' @return magpie object with a completed dataset
 #'
-
 convertStrefler <- function(x, subtype) {
 
   if (subtype == "weathering_graderegi") {

R/imports.R

@@ -1,4 +1,4 @@
 # Generated by lucode2: do not edit by hand
 
-#' @import madrat magclass mrdrivers mrcommons edgeTransport
+#' @import edgeTransport madrat magclass mrcommons mrdrivers
 NULL

R/readIEA_ETP.R

@@ -2,7 +2,6 @@
 #'
 #' @author Falk Benke
 #' @param subtype data subtype. Either "industry", "buildings", "summary", or "transport"
-#' @param useCorrected boolean indicating if the corrected version of the input sheet should be used
 #' @importFrom tibble tibble
 #' @importFrom dplyr bind_rows bind_cols select mutate
 #' @importFrom readxl read_xlsx
@@ -14,6 +13,7 @@ readIEA_ETP <- function(subtype) {
 
   region <- NULL
 
+  # nolint start
   subtypes <- list(
     industry = {
       list(
@@ -518,7 +518,7 @@ readIEA_ETP <- function(subtype) {
       )
     }
   )
-
+  # nolint end
   # ---- guardians ----
   if (!subtype %in% names(subtypes)) {
     stop(
@@ -564,8 +564,8 @@ readIEA_ETP <- function(subtype) {
   # set all 2055 data (for RTS/OECD/Chemicals with feedstocks) to NA due to faulty data in source
   if (subtype == "industry") {
     tmp[, 2055, "RTS.Industry|Chemicals and petrochemicals - final energy consumption and chemical feedstock|",
-      pmatch = T
-    ]["OECD",,] <- NA
+      pmatch = TRUE
+    ]["OECD", , ] <- NA
   }
 
   return(tmp)

README.md

@@ -1,6 +1,6 @@
 # MadRat REMIND Input Data Package
 
-R package **mrremind**, version **0.175.5**
+R package **mrremind**, version **0.175.6**
 
 [![CRAN status](https://www.r-pkg.org/badges/version/mrremind)](https://cran.r-project.org/package=mrremind)  [![R build status](https://github.com/pik-piam/mrremind/workflows/check/badge.svg)](https://github.com/pik-piam/mrremind/actions) [![codecov](https://codecov.io/gh/pik-piam/mrremind/branch/master/graph/badge.svg)](https://app.codecov.io/gh/pik-piam/mrremind) [![r-universe](https://pik-piam.r-universe.dev/badges/mrremind)](https://pik-piam.r-universe.dev/builds)
 
@@ -39,7 +39,7 @@ In case of questions / problems please contact Lavinia Baumstark <lavinia@pik-po
 
 To cite package **mrremind** in publications use:
 
-Baumstark L, Rodrigues R, Levesque A, Oeser J, Bertram C, Mouratiadou I, Malik A, Schreyer F, Soergel B, Rottoli M, Mishra A, Dirnaichner A, Pehl M, Giannousakis A, Klein D, Strefler J, Feldhaus L, Brecha R, Rauner S, Dietrich J, Bi S, Benke F, Weigmann P, Richters O, Hasse R, Fuchs S, Mandaroux R (2024). _mrremind: MadRat REMIND Input Data Package_. R package version 0.175.5, <https://github.com/pik-piam/mrremind>.
+Baumstark L, Rodrigues R, Levesque A, Oeser J, Bertram C, Mouratiadou I, Malik A, Schreyer F, Soergel B, Rottoli M, Mishra A, Dirnaichner A, Pehl M, Giannousakis A, Klein D, Strefler J, Feldhaus L, Brecha R, Rauner S, Dietrich J, Bi S, Benke F, Weigmann P, Richters O, Hasse R, Fuchs S, Mandaroux R (2024). _mrremind: MadRat REMIND Input Data Package_. R package version 0.175.6, <https://github.com/pik-piam/mrremind>.
 
 A BibTeX entry for LaTeX users is
 
@@ -48,7 +48,7 @@ A BibTeX entry for LaTeX users is
   title = {mrremind: MadRat REMIND Input Data Package},
   author = {Lavinia Baumstark and Renato Rodrigues and Antoine Levesque and Julian Oeser and Christoph Bertram and Ioanna Mouratiadou and Aman Malik and Felix Schreyer and Bjoern Soergel and Marianna Rottoli and Abhijeet Mishra and Alois Dirnaichner and Michaja Pehl and Anastasis Giannousakis and David Klein and Jessica Strefler and Lukas Feldhaus and Regina Brecha and Sebastian Rauner and Jan Philipp Dietrich and Stephen Bi and Falk Benke and Pascal Weigmann and Oliver Richters and Robin Hasse and Sophie Fuchs and Rahel Mandaroux},
   year = {2024},
-  note = {R package version 0.175.5},
+  note = {R package version 0.175.6},
   url = {https://github.com/pik-piam/mrremind},
 }
 ```