Implement explicit scenario choice across package.

.buildlibrary

@@ -1,4 +1,4 @@
-ValidationKey: '3019950'
+ValidationKey: '3222080'
 AutocreateReadme: yes
 AcceptedWarnings:
 - 'Warning: package ''.*'' was built under R version'

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: 'mrindustry: input data generation for the REMIND industry module'
-version: 0.15.0
-date-released: '2025-02-14'
+version: 0.16.0
+date-released: '2025-02-19'
 abstract: The mrindustry packages contains data preprocessing for the REMIND model.
 authors:
 - family-names: Benke

DESCRIPTION

@@ -1,8 +1,8 @@
 Type: Package
 Package: mrindustry
 Title: input data generation for the REMIND industry module
-Version: 0.15.0
-Date: 2025-02-14
+Version: 0.16.0
+Date: 2025-02-19
 Authors@R: c(
     person(given = "Falk", family = "Benke", email = "[email protected]",
            role = c("aut", "cre")),

NAMESPACE

@@ -18,7 +18,6 @@ export(calcindustry_subsectors_specific)
 export(convertADVANCE_WP2)
 export(convertMueller)
 export(convertUNIDO)
-export(convertUSGS)
 export(readADVANCE_WP2)
 export(readIEA_WEIO_2014)
 export(readMueller)
@@ -39,9 +38,6 @@ importFrom(GDPuc,convertGDP)
 importFrom(assertr,assert)
 importFrom(assertr,in_set)
 importFrom(assertr,not_na)
-importFrom(assertr,verify)
-importFrom(assertr,within_bounds)
-importFrom(dplyr,across)
 importFrom(dplyr,anti_join)
 importFrom(dplyr,arrange)
 importFrom(dplyr,as_tibble)
@@ -93,7 +89,6 @@ importFrom(ggplot2,scale_shape_manual)
 importFrom(ggplot2,theme)
 importFrom(ggplot2,theme_minimal)
 importFrom(madrat,toolCountryFill)
-importFrom(madrat,toolGetMapping)
 importFrom(magclass,"getNames<-")
 importFrom(magclass,"getYears<-")
 importFrom(magclass,add_dimension)
@@ -133,7 +128,6 @@ importFrom(readr,cols)
 importFrom(readr,read_csv)
 importFrom(readr,read_delim)
 importFrom(readr,read_rds)
-importFrom(readr,write_rds)
 importFrom(readxl,excel_sheets)
 importFrom(readxl,read_excel)
 importFrom(rlang,"!!!")

R/UNIDO.R

@@ -3,12 +3,14 @@
 #' Read and convert data from United Nations Industrial Organisation.
 #'
 #' @md
-#' @param subtype one of
-#'     - `INDSTAT2`: read INDSTAT 2 data
-#'     - `INDSTAT3`: read INDSTAT 3 data from [https://stat.unido.org/data/download?dataset=indstat&revision=3]
-#'     - `INDSTAT4`: read INDSTAT 4 data from [https://stat.unido.org/data/download?dataset=indstat&revision=4]
+#' @param subtype A string. One of:
+#' \itemize{
+#'   \item "INDSTAT2": read INDSTAT 2 data
+#'   \item "INDSTAT3": read INDSTAT 3 data from [here](https://stat.unido.org/data/download?dataset=indstat&revision=3)
+#'   \item "INDSTAT4": read INDSTAT 4 data from [here](https://stat.unido.org/data/download?dataset=indstat&revision=4)
 #'       INDSTAT 4 data quality has not been vetted and should not be used for
 #'       production.
+#' }
 #' @param exclude Exclude faulty data (`TRUE`, default) or not.  Return a tibble
 #'     of country/subsector/year combinations for `exclude = 'return'`.
 #'     (Work-in-progress)
@@ -72,7 +74,6 @@
 #'
 #' @seealso [`readSource()`], [`calcOutput()`]
 #'
-#' @importFrom assertr assert not_na verify
 #' @importFrom dplyr anti_join between bind_rows filter group_by inner_join
 #'     left_join mutate n select summarise ungroup
 #' @importFrom GDPuc convertGDP
@@ -84,7 +85,7 @@
 #' @importFrom rlang !!! .data is_empty syms
 #' @importFrom tibble tibble tribble
 #' @importFrom tidyr drop_na expand_grid unite
-
+#'
 #' @rdname UNIDO
 #' @export
 readUNIDO <- function(subtype = 'INDSTAT3')
@@ -260,7 +261,7 @@ convertUNIDO <- function(x, subtype = 'INDSTAT3', exclude = TRUE)
                 c('country' = 'un')
             ) %>%
             select(-'country') %>%
-            assert(not_na, everything())
+          assertr::assert(assertr::not_na, everything())
 
     }
 

R/calcCementShare.R

@@ -1,9 +1,9 @@
 #' Calculate Cement Share in NONMET FE Use
 #'
 #' Estimated shares of cement in `NONMET` final energy use based on OECD and
-#' Non-OECD figures from IEA 2017 [Energy Technology Perspectives](
-#' https://www.zotero.org/groups/52011/rd3/items/X8XCUJ5U).  Shares are weighted
-#' by GDP for aggregation and converge towards global values by 2100.
+#' Non-OECD figures from IEA 2017
+#' [Energy Technology Perspectives](https://www.zotero.org/groups/52011/rd3/items/X8XCUJ5U).
+#' Shares are weighted by GDP for aggregation and converge towards global values by 2100.
 #'
 #' @md
 #' @return A list with a [`magpie`][magclass::magclass] object `x`, `weight`,
@@ -60,9 +60,8 @@ calcCementShare <- function() {
     select('iso3c', 'year', 'fety', 'value') %>%
     as.magpie(spatial = 1, temporal = 2, data = 4),
 
-  weight = calcOutput('GDP', scenario = "SSP2", naming = "scenario", aggregate = FALSE) %>%
-    `[`(, unique(quitte::remind_timesteps$period), ) %>%
-    dimSums(dim = 3),
+  weight = calcOutput("GDP", scenario = "SSP2", aggregate = FALSE, years = unique(quitte::remind_timesteps$period)) %>%
+    collapseDim(dim = 3),
 
   unit = 'share',
   description = 'Share of Cement in NONMET FE use',

R/calcChemicalFeedstocksShare.R

@@ -11,15 +11,14 @@
 #'
 #' @seealso [`calcOutput()`]
 #'
-#' @importFrom assertr assert not_na
 #' @importFrom dplyr filter group_by inner_join mutate pull select summarise
 #' @importFrom quitte character.data.frame interpolate_missing_periods_
 #' @importFrom rlang .data sym
 #' @importFrom tibble as_tibble
 #' @importFrom tidyr complete everything nesting
 #' @importFrom magclass collapseDim
-
 #' @export
+#'
 calcChemicalFeedstocksShare <- function()
 {
   region_mapping <- toolGetMapping(
@@ -82,20 +81,18 @@ calcChemicalFeedstocksShare <- function()
       value = 'share', expand.values = TRUE) %>%
     full_join(region_mapping, 'region') %>%
     select('iso3c', 'year', 'share') %>%
-    assert(not_na, everything())
+    assertr::assert(assertr::not_na, everything())
 
-  weight <- calcOutput('GDP', scenario = "SSP2", naming = "scenario", aggregate = FALSE) %>%
-    dimSums(dim = 3)
+  weight <- calcOutput("GDP", scenario = "SSP2", aggregate = FALSE) %>%
+    collapseDim(dim = 3)
 
   return(
     list(
     x = x %>%
       filter(.data$year %in% unique(quitte::remind_timesteps$period)) %>%
       as.magpie(spatial = 1, temporal = 2, tidy = TRUE) %>%
       collapseDim(dim = 3),
-
-    weight = weight[,unique(quitte::remind_timesteps$period),],
-
+    weight = weight[, unique(quitte::remind_timesteps$period), ],
     unit = 'share',
     description = 'Share of feedstocks in chemicals FE input',
     min = 0, max = 1)