Merge branch 'master' of https://github.com/pik-piam/mrremind

.buildlibrary

@@ -1,4 +1,4 @@
-ValidationKey: '34720077'
+ValidationKey: '34746870'
 AcceptedWarnings:
 - 'Warning: package ''.*'' was built under R version'
 - 'Warning: namespace ''.*'' is not available and has been replaced'

.pre-commit-config.yaml

@@ -15,7 +15,7 @@ repos:
     -   id: mixed-line-ending
 
 -   repo: https://github.com/lorenzwalthert/precommit
-    rev: v0.3.2.9025
+    rev: v0.4.0
     hooks:
     -   id: parsable-R
     -   id: deps-in-desc

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: 0.175.7
-date-released: '2024-02-08'
+version: 0.175.8
+date-released: '2024-02-12'
 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: 0.175.7
-Date: 2024-02-08
+Version: 0.175.8
+Date: 2024-02-12
 Authors@R: c(
     person("Lavinia", "Baumstark", , "[email protected]", role = c("aut", "cre")),
     person("Renato", "Rodrigues", role = "aut"),

R/calcFE.R

@@ -6,15 +6,14 @@
 #' @importFrom stats na.omit
 #' @param source "IEA" or "IEA_WEO"
 #' @param scenario_proj "SSP2" by default unless overwritten
+#' @param ieaVersion Release version of IEA data, either 'default' (vetted and used in REMIND)
+#' or 'latest'.
 
-
-calcFE <- function(source = "IEA", scenario_proj = "SSP2") {
+calcFE <- function(source = "IEA", scenario_proj = "SSP2", ieaVersion = "default") {
   #------ READ-IN DATA----------------------------------------
   if (source == "IEA") {
-    data <- calcOutput("IO", subtype = "output", aggregate = FALSE)
-
-    # remove period where only 0s appear
-    data <- data[, 2021, , invert = T]
+    data <- calcOutput("IO", subtype = "output", ieaVersion = ieaVersion,
+                       aggregate = FALSE)
 
     mapping <- toolGetMapping(type = "sectoral",
                               name = "structuremappingIO_reporting.csv",
@@ -28,7 +27,7 @@ calcFE <- function(source = "IEA", scenario_proj = "SSP2") {
     colnames(map) <- gsub("io", "names_in", colnames(map))
 
     # Give description
-    descript <- "IEA Final Energy Data based on 2017 version of IEA Energy Balances"
+    descript <- "IEA Final Energy Data based on 2022 version of IEA Energy Balances"
 
     #------ PROCESS DATA ------------------------------------------
     # select data that have names
@@ -129,7 +128,6 @@ calcFE <- function(source = "IEA", scenario_proj = "SSP2") {
   } else if (source == "IEA_WEO") {
     data <- readSource(type = "IEA_WEO", subtype = "FE")
     regions <- toolGetMapping(getConfig()[1], where = "mappingfolder", type = "regional")
-    # regions <- unique(regions$RegionCode)
 
     # gdp of all countries in 2015
     gdp <- calcOutput("GDPPast", years = 2015, aggregate = FALSE)
@@ -140,7 +138,7 @@ calcFE <- function(source = "IEA", scenario_proj = "SSP2") {
     var <- getNames(data)[1]
     data_new <- new.magpie(getRegions(data), years = getYears(data), names = getNames(data), fill = NA)
     for (i in regions$CountryCode) {
-      if (!is.na(data[i, "y2010", var]) & gdp[i, , ] > 0.9 * dimSums(gdp[regions[regions$RegionCode == regions[regions$CountryCode == i, ]$RegionCode, ]$CountryCode, , ], dim = 1)) {
+      if (!is.na(data[i, "y2010", var]) && gdp[i, , ] > 0.9 * dimSums(gdp[regions[regions$RegionCode == regions[regions$CountryCode == i, ]$RegionCode, ]$CountryCode, , ], dim = 1)) {
         data_new[i, , ] <- data[i, , ]
         countries <- regions[regions$RegionCode == regions[regions$CountryCode == i, ]$RegionCode, ]$CountryCode
         data_new[setdiff(countries, i), , ] <- 0 # countries other than the "main" country
@@ -151,9 +149,7 @@ calcFE <- function(source = "IEA", scenario_proj = "SSP2") {
     data <- data_new
 
     data <- data[, , ] * 4.1868e-2 # Mtoe to EJ
-    # data <- collapseNames(data)
-    # vars <- c("Coal","Oil","Gas")
-    # data <- data[,,vars,pmatch=T]
+
     # converting to remind convention
     getNames(data) <- gsub(pattern = "Final Energy", replacement = "FE", x = getNames(data))
     getNames(data) <- paste0(getNames(data), " (EJ/yr)")

R/calcHistorical.R

@@ -6,7 +6,7 @@
 calcHistorical <- function() {
 
   # Final Energy
-  fe_iea <- calcOutput("FE", source = "IEA", aggregate = FALSE)
+  fe_iea <- calcOutput("FE", source = "IEA", ieaVersion = "latest", aggregate = FALSE)
   fe_iea <- add_dimension(fe_iea, dim = 3.1, add = "model", nm = "IEA")
 
   fe_weo <- calcOutput("FE", source = "IEA_WEO", aggregate = FALSE)
@@ -15,7 +15,7 @@ calcHistorical <- function() {
   fe_weo <- add_dimension(fe_weo, dim = 3.1, add = "model", nm = "IEA_WEO")
 
   # Primary Energy
-  pe_iea <- calcOutput("PE", subtype = "IEA", aggregate = FALSE)
+  pe_iea <- calcOutput("PE", subtype = "IEA", ieaVersion = "latest", aggregate = FALSE)
   pe_iea <- add_dimension(pe_iea, dim = 3.1, add = "model", nm = "IEA")
 
   pe_weo <- calcOutput("PE", subtype = "IEA_WEO", aggregate = FALSE)

R/calcIO.R

@@ -11,6 +11,8 @@
 #'
 #' @md
 #' @param subtype Data subtype. See default argument for possible values.
+#' @param ieaVersion Release version of IEA data, either 'default'
+#' (vetted and used in REMIND) or 'latest'.
 #' @return IEA data as MAgPIE object aggregated to country level
 #' @author Anastasis Giannousakis
 #' @seealso \code{\link{calcOutput}}
@@ -24,7 +26,9 @@
 #' @importFrom tidyr unite
 #' @importFrom tidyselect all_of
 calcIO <- function(subtype = c("input", "output", "output_biomass", "trade",
-                               "input_Industry_subsectors", "output_Industry_subsectors", "IEA_output", "IEA_input")) {
+                               "input_Industry_subsectors", "output_Industry_subsectors",
+                               "IEA_output", "IEA_input"),
+                   ieaVersion = "default") {
   subtype <- match.arg(subtype)
   switch(
     subtype,
@@ -74,8 +78,14 @@ calcIO <- function(subtype = c("input", "output", "output_biomass", "trade",
   mapping <- toolGetMapping(type = "sectoral", name = mapping, where = where,
                             returnPathOnly = TRUE)
 
+  if (!(ieaVersion %in% c("default", "latest"))) {
+    stop("Invalid parameter `ieaVersion`. Must be either 'default' or 'latest'")
+  }
+
+  ieaSubtype <- if (ieaVersion == "default") "EnergyBalances" else "EnergyBalances-latest"
+
   # read in data and convert from ktoe to EJ
-  data <- readSource("IEA", subtype = "EnergyBalances") * 4.1868e-5
+  data <- readSource("IEA", subtype = ieaSubtype) * 4.1868e-5
 
   ieamatch <- read.csv2(mapping, stringsAsFactors = FALSE, na.strings = "")
 
@@ -94,29 +104,31 @@ calcIO <- function(subtype = c("input", "output", "output_biomass", "trade",
                                                       threshold = 1e-2)
     # warn if dimensions not present in the mapping have been added to the data
     new_product_flows <- tibble(
-      text = setdiff(getNames(data), names_data_before)) %>%
-      separate('text', c('product', 'flow'), sep = '\\.') %>%
+      text = setdiff(getNames(data), names_data_before)
+    ) %>%
+      separate("text", c("product", "flow"), sep = "\\.") %>%
       anti_join(
         ieamatch %>%
           as_tibble() %>%
-          select(product = 'iea_product', flow = 'iea_flows'),
+          select(product = "iea_product", flow = "iea_flows"),
 
-        c('product', 'flow')
+        c("product", "flow")
       ) %>%
-      unite('text', c('product', 'flow'), sep = '.') %>%
-      pull('text')
+      unite("text", c("product", "flow"), sep = ".") %>%
+      pull("text")
 
     if (!is_empty(new_product_flows)) {
-      warning('Product/flow combinations not present in mapping added by ',
-           'fix_IEA_data_for_Industry_subsectors():\n',
-           paste(new_product_flows, collapse = '\n'))
+      warning("Product/flow combinations not present in mapping added by ",
+        "fix_IEA_data_for_Industry_subsectors():\n",
+        paste(new_product_flows, collapse = "\n")
+      )
     }
 
     # FIXME remove product/flow combinations from the mapping that have been
     # removed from the data while replacing coke oven and blast furnace outputs
     ieamatch <- ieamatch %>%
       as_tibble() %>%
-      filter(paste(.data$iea_product, .data$iea_flows, sep = '.')
+      filter(paste(.data$iea_product, .data$iea_flows, sep = ".")
              %in% getNames(data))
   }
 
@@ -126,7 +138,7 @@ calcIO <- function(subtype = c("input", "output", "output_biomass", "trade",
     select(all_of(c("iea_product", "iea_flows", "Weight", target))) %>%
     na.omit() %>%
     unite("target", all_of(target), sep = ".", remove = FALSE) %>%
-    unite('product.flow', c('iea_product', 'iea_flows'),sep = '.') %>%
+    unite("product.flow", c("iea_product", "iea_flows"), sep = ".") %>%
     filter(!!sym("product.flow") %in% getNames(data))
   magpieNames <- ieamatch[["target"]] %>% unique()
 
@@ -144,29 +156,29 @@ calcIO <- function(subtype = c("input", "output", "output_biomass", "trade",
            function(item) {
              product_flow <- ieamatch %>%
                filter(item == .data$target) %>%
-               pull('product.flow')
+               pull("product.flow")
 
              weights <- ieamatch %>%
                filter(item == .data$target) %>%
-               pull('Weight') %>%
+               pull("Weight") %>%
                as.numeric()
 
-             tmp <- dimSums(  data[,,product_flow]
+             tmp <- dimSums(data[, , product_flow]
                             * setNames(as.magpie(weights), product_flow),
                             dim = 3, na.rm = TRUE)
              getNames(tmp) <- item
 
              return(tmp)
-             })
+           })
   )
 
   # Split residential Biomass into traditional and modern biomass depending upon the income per capita
   if (subtype %in% c("output", "input", "output_Industry_subsectors")) {
     # In order to split the REMIND technology biotr between biotr and biotrmod,
     # We use the traditional biomass split for EDGE buildings and divide by the total quantity of FE biomass
 
-    edgeBio <- calcOutput("IOEdgeBuildings", subtype = "output_EDGE_buildings", aggregate = FALSE)
-    feBio <- calcOutput("IO", subtype = "output_biomass", aggregate = FALSE)
+    edgeBio <- calcOutput("IOEdgeBuildings", subtype = "output_EDGE_buildings", ieaVersion = ieaVersion, aggregate = FALSE)
+    feBio <- calcOutput("IO", subtype = "output_biomass", ieaVersion = ieaVersion, aggregate = FALSE)
     shareBiotrad <- edgeBio[, , "biotrad"] / (feBio[, , "sesobio.fesob.tdbiosob"] + feBio[, , "sesobio.fesoi.tdbiosoi"])
     shareBiotrad[is.na(shareBiotrad)] <- 0
     reminditems <- mbind(reminditems,
@@ -225,5 +237,5 @@ calcIO <- function(subtype = c("input", "output", "output_biomass", "trade",
   }
 
   return(list(x = reminditems, weight = NULL, unit = "EJ",
-              description = "IEA SE Output Data based on 2017 edition of IEA World Energy Balances"))
+              description = "IEA SE Output Data based on 2022 edition of IEA World Energy Balances"))
 }