fix Notes in EDGE-T functions

.buildlibrary

@@ -1,4 +1,4 @@
-ValidationKey: '38546504'
+ValidationKey: '38572284'
 AcceptedWarnings:
 - 'Warning: package ''.*'' was built under R version'
 - 'Warning: namespace ''.*'' is not available and has been replaced'
@@ -10,7 +10,6 @@ AcceptedNotes:
 - unable to verify current time
 - Imports includes .* non-default packages.
 - installed size is
-- 'Undefined global functions or variables:'
 AutocreateReadme: yes
 allowLinterWarnings: yes
 enforceVersionUpdate: yes

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: 0.192.8
-date-released: '2024-09-27'
+version: 0.192.9
+date-released: '2024-09-30'
 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: 0.192.8
-Date: 2024-09-27
+Version: 0.192.9
+Date: 2024-09-30
 Authors@R: c(
     person("Lavinia", "Baumstark", , "[email protected]", role = c("aut", "cre")),
     person("Renato", "Rodrigues", role = "aut"),

R/calcEDGETransport.R

@@ -5,103 +5,106 @@
 #' @param subtype  REMIND/iterative EDGE-T input data subtypes
 #' @return REMIND/iterative EDGE-T input data for all scenario combinations
 #' @examples
-#' \dontrun{ a <- calcOutput(type = "EDGETransport", subtype = "CAPEXandNonFuelOPEX", aggregate = F)
+#' \dontrun{
+#' a <- calcOutput(type = "EDGETransport", subtype = "CAPEXandNonFuelOPEX", aggregate = F)
 #' }
-
 calcEDGETransport <- function(subtype) {
-
   x <- readSource("EDGETransport", subtype)
 
+  weightSum <- value <- NULL
+
   switch(subtype,
-         "f35_esCapCost" = {
-           weight <- readSource("EDGETransport", subtype = "weightESdemand")
-           #Rule out numerical errors after disaggregating very small numbers
-           weight[weight < 1e-5] <- 0
-           #check whether weightsum is zero for some cases
-           #if so, the values should just be aggregated equally in order to prevent zeros in the results
-           weight <- rmndt::magpie2dt(weight)
-           regMap <- toolGetMapping(getConfig("regionmapping"), type = "regional", where = "mappingfolder")
-           setnames(regMap, "CountryCode", "all_regi")
-           weight <- merge(weight, regMap[, c("all_regi", "RegionCode")], by = "all_regi")
-           weight[, weightSum := sum(value), by = c("RegionCode", "GDP_scenario", "DEM_scenario", "EDGE_scenario", "all_teEs", "tall")]
-           weight[weightSum == 0, value := 1]
-           weight[, c("RegionCode", "weightSum") := NULL]
-           weight <- as.magpie(weight)
-           unit = "2017US$/(p|t)km"
-           description = "Capital cost (purchase) per energy service demand on CES level."
-         },
-         "f35_fe2es" = {
-           weight = readSource("EDGETransport", "f35_demByTech")
-           weight[weight < 1e-5] <- 0
-           #check whether weightsum is zero for some cases
-           #if so, the values should just be aggregated equally in order to prevent zeros in the results
-           weight <- rmndt::magpie2dt(weight)
-           regMap <- toolGetMapping(getConfig("regionmapping"), type = "regional", where = "mappingfolder")
-           setnames(regMap, "CountryCode", "all_regi")
-           weight <- merge(weight, regMap[, c("all_regi", "RegionCode")], by = "all_regi")
-           weight[, weightSum := sum(value), by = c("RegionCode", "GDP_scenario", "DEM_scenario", "EDGE_scenario", "all_enty", "all_in", "all_teEs", "tall")]
-           weight[weightSum == 0, value := 1]
-           weight[, c("RegionCode", "weightSum", "all_enty", "all_in") := NULL]
-           weight <- as.magpie(weight)
-           unit = "trn (p|t)km/Twa"
-           description = "Energy efficiency on CES level."
-         },
-         "f35_demByTech" = {
-           weight = NULL
-           unit = "TWa"
-           description = "Final energy demand on CES level."
-         },
-         "f29_trpdemand" = {
-           weight = NULL
-           unit = "trillion pkm/trillion tkm"
-           description = "Energy service demand on CES level."
-         },
-         "CAPEXandNonFuelOPEX" = {
-           gdp <- calcOutput("GDP", aggregate = FALSE)[,,"gdp_SSP2"]
-           weight = gdp |> time_interpolate(getYears(x))
-           unit = "2017US$/(p|t)km"
-           description = "Capital cost (purchase) and non-fuel operational costs on technology level."
-         },
-         "scenSpecPrefTrends" = {
-           gdp <- calcOutput("GDP", aggregate = FALSE)[,,"gdp_SSP2"]
-           weight = gdp |> time_interpolate(getYears(x))
-           unit = "-"
-           description = "Scenario specific preference trends on technology level."
-         },
-         "scenSpecLoadFactor" = {
-           gdp <- calcOutput("GDP", aggregate = FALSE)[,,"gdp_SSP2"]
-           weight = gdp |> time_interpolate(getYears(x))
-           unit = "-"
-           description = "Scenario specific load factor on technology level."
-         },
-         "scenSpecEnIntensity" = {
-           gdp <- calcOutput("GDP", aggregate = FALSE)[,,"gdp_SSP2"]
-           weight = gdp |> time_interpolate(getYears(x))
-           unit = "MJ/vehkm"
-           description = "Scenario specific energy intensity on technology level."
-         },
-         "initialIncoCosts" = {
-           gdp <- calcOutput("GDP", aggregate = FALSE)[,,"gdp_SSP2"]
-           weight = gdp |> time_interpolate(getYears(x))
-           unit = "2017US$/(p|t)km"
-           description = "Initial inconvenience cost values."
-         },
-         "annualMileage" = {
-           gdp <- calcOutput("GDP", aggregate = FALSE)[,,"gdp_SSP2"]
-           weight = gdp |> time_interpolate(getYears(x))
-           unit = "vehkm/yr"
-           description = "Annual vehicle km traveled."
-         },
-         "timeValueCosts" = {
-           gdp <- calcOutput("GDP", aggregate = FALSE)[,,"gdp_SSP2"]
-           weight = gdp |> time_interpolate(getYears(x))
-           unit = "2017US$/(p|t)km"
-           description = "Value of time cost equivalent."
-         }
-       )
+    "f35_esCapCost" = {
+      weight <- readSource("EDGETransport", subtype = "weightESdemand")
+      # Rule out numerical errors after disaggregating very small numbers
+      weight[weight < 1e-5] <- 0
+      # check whether weightsum is zero for some cases
+      # if so, the values should just be aggregated equally in order to prevent zeros in the results
+      weight <- rmndt::magpie2dt(weight)
+      regMap <- toolGetMapping(getConfig("regionmapping"), type = "regional", where = "mappingfolder")
+      setnames(regMap, "CountryCode", "all_regi")
+      weight <- merge(weight, regMap[, c("all_regi", "RegionCode")], by = "all_regi")
+      weight[, weightSum := sum(value), by = c("RegionCode", "GDP_scenario", "DEM_scenario", "EDGE_scenario", "all_teEs", "tall")]
+      weight[weightSum == 0, value := 1]
+      weight[, c("RegionCode", "weightSum") := NULL]
+      weight <- as.magpie(weight)
+      unit <- "2017US$/(p|t)km"
+      description <- "Capital cost (purchase) per energy service demand on CES level."
+    },
+    "f35_fe2es" = {
+      weight <- readSource("EDGETransport", "f35_demByTech")
+      weight[weight < 1e-5] <- 0
+      # check whether weightsum is zero for some cases
+      # if so, the values should just be aggregated equally in order to prevent zeros in the results
+      weight <- rmndt::magpie2dt(weight)
+      regMap <- toolGetMapping(getConfig("regionmapping"), type = "regional", where = "mappingfolder")
+      setnames(regMap, "CountryCode", "all_regi")
+      weight <- merge(weight, regMap[, c("all_regi", "RegionCode")], by = "all_regi")
+      weight[, weightSum := sum(value), by = c("RegionCode", "GDP_scenario", "DEM_scenario", "EDGE_scenario", "all_enty", "all_in", "all_teEs", "tall")]
+      weight[weightSum == 0, value := 1]
+      weight[, c("RegionCode", "weightSum", "all_enty", "all_in") := NULL]
+      weight <- as.magpie(weight)
+      unit <- "trn (p|t)km/Twa"
+      description <- "Energy efficiency on CES level."
+    },
+    "f35_demByTech" = {
+      weight <- NULL
+      unit <- "TWa"
+      description <- "Final energy demand on CES level."
+    },
+    "f29_trpdemand" = {
+      weight <- NULL
+      unit <- "trillion pkm/trillion tkm"
+      description <- "Energy service demand on CES level."
+    },
+    "CAPEXandNonFuelOPEX" = {
+      gdp <- calcOutput("GDP", aggregate = FALSE)[, , "gdp_SSP2"]
+      weight <- gdp |> time_interpolate(getYears(x))
+      unit <- "2017US$/(p|t)km"
+      description <- "Capital cost (purchase) and non-fuel operational costs on technology level."
+    },
+    "scenSpecPrefTrends" = {
+      gdp <- calcOutput("GDP", aggregate = FALSE)[, , "gdp_SSP2"]
+      weight <- gdp |> time_interpolate(getYears(x))
+      unit <- "-"
+      description <- "Scenario specific preference trends on technology level."
+    },
+    "scenSpecLoadFactor" = {
+      gdp <- calcOutput("GDP", aggregate = FALSE)[, , "gdp_SSP2"]
+      weight <- gdp |> time_interpolate(getYears(x))
+      unit <- "-"
+      description <- "Scenario specific load factor on technology level."
+    },
+    "scenSpecEnIntensity" = {
+      gdp <- calcOutput("GDP", aggregate = FALSE)[, , "gdp_SSP2"]
+      weight <- gdp |> time_interpolate(getYears(x))
+      unit <- "MJ/vehkm"
+      description <- "Scenario specific energy intensity on technology level."
+    },
+    "initialIncoCosts" = {
+      gdp <- calcOutput("GDP", aggregate = FALSE)[, , "gdp_SSP2"]
+      weight <- gdp |> time_interpolate(getYears(x))
+      unit <- "2017US$/(p|t)km"
+      description <- "Initial inconvenience cost values."
+    },
+    "annualMileage" = {
+      gdp <- calcOutput("GDP", aggregate = FALSE)[, , "gdp_SSP2"]
+      weight <- gdp |> time_interpolate(getYears(x))
+      unit <- "vehkm/yr"
+      description <- "Annual vehicle km traveled."
+    },
+    "timeValueCosts" = {
+      gdp <- calcOutput("GDP", aggregate = FALSE)[, , "gdp_SSP2"]
+      weight <- gdp |> time_interpolate(getYears(x))
+      unit <- "2017US$/(p|t)km"
+      description <- "Value of time cost equivalent."
+    }
+  )
 
-  return(list(x           = x,
-              weight      = weight,
-              unit        = unit,
-              description = description))
+  return(list(
+    x = x,
+    weight = weight,
+    unit = unit,
+    description = description
+  ))
 }

R/calcFeDemandTransport.R

@@ -2,7 +2,6 @@
 #'
 #' @author Alois Dirnaicher, Johanna Hoppe
 calcFeDemandTransport <- function() {
-
   # Read in stationary data and map to REMIND variables ----
 
   # REMIND transport items
@@ -74,7 +73,7 @@ calcFeDemandTransport <- function() {
     select("scenario", "region", "year" = "period", "item", "value") %>%
     filter(.data$scenario == "gdp_SSP2") %>%
     mutate("scenario" = "gdp_SDP") %>%
-    as.data.table()
+    data.table::as.data.table()
 
   ## get population
   pop <- data.table::as.data.table(calcOutput("Population"))[

R/convertEDGETransport.R

@@ -7,26 +7,28 @@
 #' @importFrom madrat toolAggregate
 #' @author Johanna Hoppe
 
-convertEDGETransport = function(x, subtype) {
+convertEDGETransport <- function(x, subtype) {
+
+  RegionCode <- CountryCode <- . <- NULL
 
   mappingfile <- setDT(toolGetMapping("regionmapping_21_EU11.csv", type = "regional",
                                       where = "mappingfolder"))[, .(iso = CountryCode, region = RegionCode)]
   if (subtype %in% c("f35_demByTech", "f29_trpdemand", "weightESdemand")) {
     gdp <- calcOutput("GDP", aggregate = FALSE) |> time_interpolate(getYears(x), extrapolation_type = "constant")
-    gdp <- gdp[,,"gdp_SSP2"]
+    gdp <- gdp[, , "gdp_SSP2"]
     result <- toolAggregate(x = x, weight = gdp, rel = mappingfile, from = "region", to = "iso")
   } else if (!subtype == "shares_LDV_transport") {
     result <- toolAggregate(x = x, rel = mappingfile, weight = NULL, from = "region", to = "iso")
   } else if (subtype %in% c("shares_LDV_transport")) {
     ## only the first EDGE-T scenario for SSP2 is used as a proxy for the LDV shares
-    x <- x[,, "gdp_SSP2.Mix1.gdp_SSP2.share_LDV_totliq.shares_LDV_transport"]
+    x <- x[, , "gdp_SSP2.Mix1.gdp_SSP2.share_LDV_totliq.shares_LDV_transport"]
 
-    for (year in getYears(x, as.integer = T)){
-      x[,year,] <- as.vector(x[,c(2010),]) + ((0.55 - as.vector(x[,c(2010),]))/(2100-2010))*(year-2010)
+    for (year in getYears(x, as.integer = TRUE)) {
+      x[, year, ] <- as.vector(x[, c(2010), ]) + ((0.55 - as.vector(x[, c(2010), ])) / (2100 - 2010)) * (year - 2010)
     }
-    #extending values
-    x <- time_interpolate(x, integrate_interpolated_years=T, interpolated_year = seq(from = 1990, to = 2100), extrapolation_type = "linear")
-    x <- time_interpolate(x, integrate_interpolated_years=T, interpolated_year = c(seq(from = 1970, to = 1989),seq(from = 2101, to = 2150)), extrapolation_type = "constant")
+    # extending values
+    x <- time_interpolate(x, integrate_interpolated_years = TRUE, interpolated_year = seq(from = 1990, to = 2100), extrapolation_type = "linear")
+    x <- time_interpolate(x, integrate_interpolated_years = TRUE, interpolated_year = c(seq(from = 1970, to = 1989), seq(from = 2101, to = 2150)), extrapolation_type = "constant")
     result <- x
   }
   return(result)

R/readEDGETransport.R

@@ -9,14 +9,16 @@
 #' @param subtype REMIND/iterative EDGE-T input data subtypes
 #'
 #' @examples
-#' \dontrun{ a <- readSource(type = "EDGETransport")
+#' \dontrun{
+#' a <- readSource(type = "EDGETransport")
 #' }
 #' @importFrom tidyr expand_grid
 #' @importFrom dplyr bind_rows
 #' @importFrom data.table data.table rbindlist := setnames setkeyv
 
 readEDGETransport <- function(subtype) {
 
+  EDGE_scenario <- DEM_scenario <- NULL
   #############################################################
   ## Define all scenario combinations for which
   ## input data should be generated
@@ -33,32 +35,32 @@ readEDGETransport <- function(subtype) {
     # Specific project scenarios
     tribble(
       ~SSPscen,         ~transportPolScen,        ~isICEban,    ~demScen,
-      'SSP1',          'Mix1',                    FALSE,      'default',
-      'SSP1',          'Mix2',                    FALSE,      'default',
-      'SSP1',          'Mix3',                    TRUE,       'default',
-      'SSP1',          'Mix4',                    TRUE,       'default',
-      'SSP2',          'Mix1',                    FALSE,      'SSP2_demRedStrong',
-      'SSP2',          'Mix2',                    FALSE,      'SSP2_demRedStrong',
-      'SSP2',          'Mix3',                    TRUE,       'SSP2_demRedStrong',
-      'SSP2',          'Mix4',                    TRUE,       'SSP2_demRedStrong',
-      'SSP2',          'Mix4',                    TRUE,       'SSP2_demDiffer',
-      'SSP2',          'Mix1',                    FALSE,      'SSP2_demDiffer',
-      'SDP_EI',        'Mix4',                    TRUE,       'default',
-      'SDP_MC',        'Mix4',                    TRUE,       'default',
-      'SDP_RC',        'Mix3',                    TRUE,       'default',
-      'SSP2',          'HydrHype4',               TRUE,       'default',
-      'SSP2',          'NAV_act',                 FALSE,      'SSP2_demRedStrong',
-      'SSP2',          'NAV_tec',                 FALSE,      'default',
-      'SSP2',          'NAV_ele',                 TRUE,       'default',
-      'SSP2',          'NAV_all',                 TRUE,       'SSP2_demRedStrong',
-      'SSP2',          'NAV_lce',                 FALSE,      'SSP2_demRedStrong',
-      'SSP2',          'CAMP_lscWeak',            TRUE,       'SSP2_demRedWeak',
-      'SSP2',          'CAMP_lscStrong',          TRUE,       'SSP2_demRedStrong'
+      "SSP1",          "Mix1",                    FALSE,      "default",
+      "SSP1",          "Mix2",                    FALSE,      "default",
+      "SSP1",          "Mix3",                    TRUE,       "default",
+      "SSP1",          "Mix4",                    TRUE,       "default",
+      "SSP2",          "Mix1",                    FALSE,      "SSP2_demRedStrong",
+      "SSP2",          "Mix2",                    FALSE,      "SSP2_demRedStrong",
+      "SSP2",          "Mix3",                    TRUE,       "SSP2_demRedStrong",
+      "SSP2",          "Mix4",                    TRUE,       "SSP2_demRedStrong",
+      "SSP2",          "Mix4",                    TRUE,       "SSP2_demDiffer",
+      "SSP2",          "Mix1",                    FALSE,      "SSP2_demDiffer",
+      "SDP_EI",        "Mix4",                    TRUE,       "default",
+      "SDP_MC",        "Mix4",                    TRUE,       "default",
+      "SDP_RC",        "Mix3",                    TRUE,       "default",
+      "SSP2",          "HydrHype4",               TRUE,       "default",
+      "SSP2",          "NAV_act",                 FALSE,      "SSP2_demRedStrong",
+      "SSP2",          "NAV_tec",                 FALSE,      "default",
+      "SSP2",          "NAV_ele",                 TRUE,       "default",
+      "SSP2",          "NAV_all",                 TRUE,       "SSP2_demRedStrong",
+      "SSP2",          "NAV_lce",                 FALSE,      "SSP2_demRedStrong",
+      "SSP2",          "CAMP_lscWeak",            TRUE,       "SSP2_demRedWeak",
+      "SSP2",          "CAMP_lscStrong",          TRUE,       "SSP2_demRedStrong"
     )
   )
 
   # generate list from data frame rows
-  allScens <- split(allScens, seq(nrow(allScens)))
+  allScens <- split(allScens, seq_len(nrow(allScens)))
 
   #############################################################
   ## Run EDGE-Transport SA with all scenario combinations
@@ -82,7 +84,7 @@ readEDGETransport <- function(subtype) {
   # Bind rows of equally named subtypes
   EdgeTransportSAdata <- lapply(types, function(type, outerList) {
     listOfDataTables <- lapply(outerList, function(innerList) innerList[[type]])
-    result <- rbindlist(listOfDataTables)
+    rbindlist(listOfDataTables)
   }, EdgeTransportSAdata)
 
   EdgeTransportSAdata <- setNames(EdgeTransportSAdata, types)

R/readGlobalEnergyMonitor.R

@@ -29,7 +29,7 @@ readGlobalEnergyMonitor <- function() {
            c2 = "Country/area 2 (hydropower only)",
            v1 = "Country/area 1 Capacity (MW) (hydropower only)",
            v2 = "Country/area 2 Capacity (MW) (hydropower only)") %>%
-    filter(status %in% c("announced", "pre-construction", "construction", "operating")) %>%
+    filter(.data$status %in% c("announced", "pre-construction", "construction", "operating")) %>%
     # ASSUMPTION: rows with empty start year are ignored
     # only look at pipeline until 2030
     filter(!is.na(.data$start), .data$start < 2031) %>%