merge upstream

.buildlibrary

@@ -1,4 +1,4 @@
-ValidationKey: '38484600'
+ValidationKey: '38486525'
 AcceptedWarnings:
 - 'Warning: package ''.*'' was built under R version'
 - 'Warning: namespace ''.*'' is not available and has been replaced'

CITATION.cff

@@ -3,7 +3,7 @@ message: If you use this software, please cite it using the metadata from this f
 type: software
 title: 'mrremind: MadRat REMIND Input Data Package'
 version: 0.192.5
-date-released: '2024-09-26'
+date-released: '2024-09-27'
 abstract: The mrremind packages contains data preprocessing for the REMIND model.
 authors:
 - family-names: Baumstark

DESCRIPTION

@@ -2,7 +2,7 @@ Type: Package
 Package: mrremind
 Title: MadRat REMIND Input Data Package
 Version: 0.192.5
-Date: 2024-09-26
+Date: 2024-09-27
 Authors@R: c(
     person("Lavinia", "Baumstark", , "[email protected]", role = c("aut", "cre")),
     person("Renato", "Rodrigues", role = "aut"),

R/calcAGEB.R

@@ -8,16 +8,15 @@
 #' @param subtype data subtype. Either "balances" ("Auswertungstabellen zur Energiebilanz Deutschland") or
 #'        "electricity" ("Bruttostromerzeugung in Deutschland nach Energieträgern")
 #' @importFrom dplyr select mutate left_join
-#' @importFrom rlang sym
 #' @importFrom stats aggregate
 #' @export
 calcAGEB <- function(subtype = "balances") {
   ageb <- readSource("AGEB", subtype = subtype)
 
-  mapping <- toolGetMapping("Mapping_AGEB_REMIND.csv", type = "reportingVariables", where = "mappingfolder") %>%
-    mutate("conversion" = as.numeric(!!sym("Factor")) * !!sym("Weight")) %>%
+  mapping <- toolGetMapping("Mapping_AGEB_REMIND.csv", type = "reportingVariables", where = "mrremind") %>%
+    mutate("conversion" = as.numeric(.data$Factor)) %>%
     select("variable" = "AGEB_variable", "REMIND_variable", "conversion", "unit" = "Unit_AGEB", "Unit_REMIND") %>%
-    filter(!!sym("REMIND_variable") != "")
+    filter(.data$REMIND_variable != "")
 
   x <- left_join(
     ageb %>%
@@ -29,11 +28,11 @@ calcAGEB <- function(subtype = "balances") {
         "unit" = "Data2", "value" = "Value"
       ),
     mapping,
-    by = "variable"
+    by = "variable", relationship = "many-to-many"
   ) %>%
     mutate(
-      "value" = !!sym("value") * !!sym("conversion"),
-      "REMIND_variable" = paste0(!!sym("REMIND_variable"), " (", !!sym("Unit_REMIND"), ")")
+      "value" = .data$value * .data$conversion,
+      "REMIND_variable" = paste0(.data$REMIND_variable, " (", .data$Unit_REMIND, ")")
     ) %>%
     select("variable" = "REMIND_variable", "region", "year", "value")
 

R/readAGEB.R

@@ -82,21 +82,42 @@ readAGEB <- function(subtype = "balances") {
       as.magpie() %>%
       return()
   } else if (subtype == "electricity") {
-    read_xlsx(
-      path = "STRERZ_Abg_02_2024_korr.xlsx",
-      sheet = "STRERZ (brutto)", col_names = TRUE,
-      col_types = c("text", rep("numeric", 34)),
-      range = "B3:AJ17", .name_repair = "minimal", na = c("k.A.")
-    ) %>%
-      mutate("TWh" = gsub(", darunter:", "", !!sym("TWh"))) %>%
-      mutate("TWh" = gsub("- ", "", !!sym("TWh"))) %>%
-      mutate("TWh" = gsub("[0-9])", "", !!sym("TWh"))) %>%
-      mutate("variable" = paste0("9 Bruttostromerzeugung|", !!sym("TWh"))) %>%
-      select(-1) %>%
-      reshape2::melt(id.vars = c("variable"), variable.name = "period", value.name = "value") %>%
-      mutate("region" = "DEU", "unit" = "TWh") %>%
-      select("region", "period", "variable", "unit", "value") %>%
-      as.magpie() %>%
-      return()
+
+    sheets <-  tibble(
+      sheet = c("STRERZ (brutto)", "STRERZ (netto)"),
+      prefix = c("9 Bruttostromerzeugung", "10 Nettostromerzeugung")
+    )
+
+    data <- NULL
+
+    for (i in seq(1:nrow(sheets))) {
+      tmp <- read_xlsx(
+        path = "STRERZ_Abg_02_2024_korr.xlsx",
+        sheet = sheets[["sheet"]][[i]],
+        col_names = TRUE,
+        col_types = c("text", rep("numeric", 34)),
+        range = "B3:AJ23", .name_repair = "minimal", na = c("k.A.")
+      ) %>%
+        mutate("TWh" = gsub(", darunter:", "", .data$TWh)) %>%
+        mutate("TWh" = gsub("- ", "", .data$TWh)) %>%
+        mutate("TWh" = gsub("[0-9])", "", .data$TWh)) %>%
+        mutate("TWh" = trimws(.data$TWh))
+
+      tmp[12,"TWh"] <- "Erneuerbare, darunter Hausmüll"
+      tmp[16,"TWh"] <- "Sonstige, darunter Hausmüll"
+
+      tmp <- tmp %>%
+        mutate("variable" = paste0(sheets[["prefix"]][[i]], "|", .data$TWh)) %>%
+        select(-1) %>%
+        reshape2::melt(id.vars = c("variable"), variable.name = "period", value.name = "value") %>%
+        mutate("region" = "DEU", "unit" = "TWh") %>%
+        select("region", "period", "variable", "unit", "value")
+
+      data <- rbind(data, tmp)
+
+    }
+
+    return(as.magpie(data))
+
   }
 }