weight warnings

.buildlibrary

@@ -1,4 +1,4 @@
-ValidationKey: '51601536'
+ValidationKey: '51704420'
 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: 'mrvalidation: madrat data preparation for validation purposes'
-version: 2.59.2
-date-released: '2024-07-04'
+version: 2.59.3
+date-released: '2024-08-05'
 abstract: Package contains routines to prepare data for validation exercises.
 authors:
 - family-names: Bodirsky

DESCRIPTION

@@ -1,8 +1,8 @@
 Type: Package
 Package: mrvalidation
 Title: madrat data preparation for validation purposes
-Version: 2.59.2
-Date: 2024-07-04
+Version: 2.59.3
+Date: 2024-08-05
 Authors@R: c(
     person("Benjamin Leon", "Bodirsky", , "[email protected]", role = c("aut", "cre")),
     person("Stephen", "Wirth", role = "aut"),

R/calcValidGini.R

@@ -7,27 +7,27 @@
 
 calcValidGini <- function() {
 
- out <- readSource("WBPoverty", subtype = "Gini", convert = FALSE)
- getSets(out)[3] <- "scenario"
- getItems(out, dim = 3) <- "historical"
+  out <- readSource("WBPoverty", subtype = "Gini", convert = FALSE)
+  getSets(out)[3] <- "scenario"
+  getItems(out, dim = 3) <- "historical"
 
- weight <- calcOutput("Population", aggregate = FALSE)[, , "pop_SSP2"]
- weight <- time_interpolate(weight,  interpolated_year = getYears(out),
-                                    integrate_interpolated_years = TRUE)
+  weight <- calcOutput("Population", aggregate = FALSE)[, , "pop_SSP2"]
+  weight <- time_interpolate(weight, interpolated_year = getYears(out),
+                             integrate_interpolated_years = TRUE)
 
- weight <- weight[getItems(out, dim = 1), getItems(out, dim = 2), ]
- weight[which(out == 9999)] <- 0 # make missing data 0 weight
+  weight <- weight[getItems(out, dim = 1), getItems(out, dim = 2), ]
+  weight[which(out == 9999)] <- 0 # make missing data 0 weight
 
- out <- add_dimension(out, dim = 3.2, add = "model", nm = "World Bank WDI")
- getNames(out, dim = 1) <- "Income|Gini Coefficient (0-1)"
+  out <- add_dimension(out, dim = 3.2, add = "model", nm = "World Bank WDI")
+  getNames(out, dim = 1) <- "Income|Gini Coefficient (0-1)"
 
- getSets(weight)[3] <- "scenario"
- getItems(weight, dim = 3) <- "historical"
- weight <- add_dimension(weight, dim = 3.2, add = "model", nm = "World Bank WDI")
- getNames(weight, dim = 1) <- "Income|Gini Coefficient (0-1)"
+  getSets(weight)[3] <- "scenario"
+  getItems(weight, dim = 3) <- "historical"
+  weight <- add_dimension(weight, dim = 3.2, add = "model", nm = "World Bank WDI")
+  getNames(weight, dim = 1) <- "Income|Gini Coefficient (0-1)"
 
   return(list(x = out,
-              weight = weight,
+              weight = weight + 10^-10,
               unit = "(0-1) Gini Coefficient between 0 and 1",
               description = "Gini Coefficient")
   )

R/calcValidPriceIndex.R

@@ -1,8 +1,8 @@
 #' @title calcValidPriceIndex
 #'
-#' @description provides global producer price index from FAO 
-#' 
-#' @param datasource Options of the source of data:  \code{FAO}. 
+#' @description provides global producer price index from FAO
+#'
+#' @param datasource Options of the source of data:  \code{FAO}.
 #' @param value \code{real} and \code{nominal}
 #' @param baseyear Baseyear for normalizing of price index.
 #' @param round Rounding of price index to intiger numbers. Default \code{TRUE}.
@@ -12,80 +12,86 @@
 #' @seealso
 #' \code{\link{readProdPrIndex}}
 #' @examples
-#' 
-#' \dontrun{ a <- calcOutput("ValidPriceIndex", value="real", aggregate=FALSE)
+#' \dontrun{
+#' a <- calcOutput("ValidPriceIndex", value = "real", aggregate = FALSE)
 #' }
-#' 
+#'
 #' @importFrom magpiesets findset reporthelper
 #' @importFrom magclass wrap setNames
 #' @importFrom madrat toolAggregate toolGetMapping
 
-calcValidPriceIndex <- function(datasource="FAO", value="real", baseyear="y2005", round=TRUE){
-  if(datasource=="FAO"){
+calcValidPriceIndex <- function(datasource = "FAO", value = "real", baseyear = "y2005", round = TRUE) {
+  if (datasource == "FAO") {
     # FAO prices (already in dm values)
-    p_t <- calcOutput("PriceAgriculture", datasource=datasource, aggregate=FALSE)
+    pT <- calcOutput("PriceAgriculture", datasource = datasource, aggregate = FALSE)
     ## set prices p_t back to magpie names
-    p_t <- collapseNames(p_t)
-    
+    pT <- collapseNames(pT)
+
     # FAO production
-    q_t <- calcOutput("FAOharmonized", aggregate=FALSE)
-    aggregation <- toolGetMapping("FAOitems.rda","sectoral",where="mrvalidation")
-    q_t <- toolAggregate(q_t[,,"production"], rel=aggregation, from="FoodBalanceItem", 
-                    to="k", dim=3.1, partrel = TRUE, verbosity=2)
-    q_t <- collapseNames(q_t)
+    qT <- calcOutput("FAOharmonized", aggregate = FALSE)
+    aggregation <- toolGetMapping("FAOitems.rda", "sectoral", where = "mrvalidation")
+    qT <- toolAggregate(qT[, , "production"], rel = aggregation, from = "FoodBalanceItem",
+                        to = "k", dim = 3.1, partrel = TRUE, verbosity = 2)
+    qT <- collapseNames(qT)
     ## convert FAO production to DM tonnes
-    dm <- 1/readSource("ProductAttributes","Products")[,,"wm"]
+    dm <- 1 / readSource("ProductAttributes", "Products")[, , "wm"]
     dm <- collapseNames(dm)
     ### common years and names dm factors, quantities and prices
-    comms <- intersect(intersect(getNames(dm),getNames(q_t)), getNames(p_t))
-    ys <- intersect(getYears(p_t),getYears(q_t))[-1]
-    q_t <- q_t[,ys,comms]*dm[,,comms]
-    p_t <- p_t[,ys,comms]
-    
-    # create baseyear values 
-    q_0 <- q_t
-    p_0 <- p_t
-    for(y in intersect(getYears(p_t),getYears(q_t))){
-      q_0[,y,] <- setYears(q_t[,baseyear,],y)
-      p_0[,y,] <- setYears(p_t[,baseyear,],y)
+    comms <- intersect(intersect(getNames(dm), getNames(qT)), getNames(pT))
+    ys <- intersect(getYears(pT), getYears(qT))[-1]
+    qT <- qT[, ys, comms] * dm[, , comms]
+    pT <- pT[, ys, comms]
+
+    # create baseyear values
+    q0 <- qT
+    p0 <- pT
+    for (y in intersect(getYears(pT), getYears(qT))) {
+      q0[, y, ] <- setYears(qT[, baseyear, ], y)
+      p0[, y, ] <- setYears(pT[, baseyear, ], y)
     }
-    
+
     # calculate Laspeyers price index
-    out <- dimSums(p_t * q_0, dim=3, na.rm=TRUE) / dimSums(p_0 * q_0, dim=3, na.rm=TRUE)
-    
+    out <- dimSums(pT * q0, dim = 3, na.rm = TRUE) / dimSums(p0 * q0, dim = 3, na.rm = TRUE)
+
     out <- out * 100
-    out[is.nan(out)|is.infinite(out)] <- 0
-    if (round) {out <- round(out)}
-
-    out <- setNames(out,paste0("Prices|Food Price Index (Index ",sub("y","",baseyear),"=100)"))
+    out[is.nan(out) | is.infinite(out)] <- 0
+    if (round) {
+      out <- round(out)
+    }
+
+    out <- setNames(out, paste0("Prices|Food Price Index (Index ", sub("y", "", baseyear), "=100)"))
     names(dimnames(out))[3] <- "variable"
-    
-    #weithts: values of consumption at the initial time step
-    weights <- dimSums(p_0 * q_0, dim=3, na.rm=TRUE)
+
+    # weithts: values of consumption at the initial time step
+    weights <- dimSums(p0 * q0, dim = 3, na.rm = TRUE)
     names(dimnames(weights))[3] <- "variable"
     dimnames(weights)[[3]] <- "Aggregate Initial Consumption Value"
-    
+
     weight       <- weights
-    description  <- paste0("Fao Food Price Index, ",sub("y","",baseyear),"=100")
-    isocountries <- TRUE 
-    unit <- paste0("Index ",baseyear,"=100")
-    
-  } else if(datasource=="ProdPrIndex"){
-    out <- readSource(type="ProdPrIndex")
-    out <- out[,,value]
-    
+    description  <- paste0("Fao Food Price Index, ", sub("y", "", baseyear), "=100")
+    isocountries <- TRUE
+    unit <- paste0("Index ", baseyear, "=100")
+
+  } else if (datasource == "ProdPrIndex") {
+    out <- readSource(type = "ProdPrIndex")
+    out <- out[, , value]
+
     weight       <- NULL
     description  <- "Fao Food Price Index, 2002-2004=100"
     unit         <- "Index 2002-2004=100"
     isocountries <- FALSE
-  } 
-
-  out <- add_dimension(out, dim=3.1, add="scenario", nm="historical")
-  out <- add_dimension(out, dim=3.2, add="model", nm=datasource)
-
-  return(list(x=out,
-              weight=weight,
-              unit=unit,
-              description=description,
-              isocountries=isocountries))
+  }
+
+  out <- add_dimension(out, dim = 3.1, add = "scenario", nm = "historical")
+  out <- add_dimension(out, dim = 3.2, add = "model", nm = datasource)
+
+  if (!is.null(weight)) {
+    weight <- weight + 10^-10
+  }
+
+  return(list(x = out,
+              weight = weight,
+              unit = unit,
+              description = description,
+              isocountries = isocountries))
 }

README.md

@@ -1,6 +1,6 @@
 # madrat data preparation for validation purposes
 
-R package **mrvalidation**, version **2.59.2**
+R package **mrvalidation**, version **2.59.3**
 
 [![CRAN status](https://www.r-pkg.org/badges/version/mrvalidation)](https://cran.r-project.org/package=mrvalidation) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.4317826.svg)](https://doi.org/10.5281/zenodo.4317826) [![R build status](https://github.com/pik-piam/mrvalidation/workflows/check/badge.svg)](https://github.com/pik-piam/mrvalidation/actions) [![codecov](https://codecov.io/gh/pik-piam/mrvalidation/branch/master/graph/badge.svg)](https://app.codecov.io/gh/pik-piam/mrvalidation) [![r-universe](https://pik-piam.r-universe.dev/badges/mrvalidation)](https://pik-piam.r-universe.dev/builds)
 
@@ -39,7 +39,7 @@ In case of questions / problems please contact Benjamin Leon Bodirsky <bodirsky@
 
 To cite package **mrvalidation** in publications use:
 
-Bodirsky B, Wirth S, Karstens K, Humpenoeder F, Stevanovic M, Mishra A, Biewald A, Weindl I, Beier F, Chen D, Crawford M, Leip D, Molina Bacca E, Kreidenweis U, W. Yalew A, von Jeetze P, Wang X, Dietrich J, Alves M (2024). _mrvalidation: madrat data preparation for validation purposes_. doi:10.5281/zenodo.4317826 <https://doi.org/10.5281/zenodo.4317826>, R package version 2.59.2, <https://github.com/pik-piam/mrvalidation>.
+Bodirsky B, Wirth S, Karstens K, Humpenoeder F, Stevanovic M, Mishra A, Biewald A, Weindl I, Beier F, Chen D, Crawford M, Leip D, Molina Bacca E, Kreidenweis U, W. Yalew A, von Jeetze P, Wang X, Dietrich J, Alves M (2024). _mrvalidation: madrat data preparation for validation purposes_. doi:10.5281/zenodo.4317826 <https://doi.org/10.5281/zenodo.4317826>, R package version 2.59.3, <https://github.com/pik-piam/mrvalidation>.
 
 A BibTeX entry for LaTeX users is
 
@@ -48,8 +48,8 @@ A BibTeX entry for LaTeX users is
   title = {mrvalidation: madrat data preparation for validation purposes},
   author = {Benjamin Leon Bodirsky and Stephen Wirth and Kristine Karstens and Florian Humpenoeder and Mishko Stevanovic and Abhijeet Mishra and Anne Biewald and Isabelle Weindl and Felicitas Beier and David Chen and Michael Crawford and Debbora Leip and Edna {Molina Bacca} and Ulrich Kreidenweis and Amsalu {W. Yalew} and Patrick {von Jeetze} and Xiaoxi Wang and Jan Philipp Dietrich and Marcos Alves},
   year = {2024},
-  note = {R package version 2.59.2},
-  doi = {10.5281/zenodo.4317826},
+  note = {R package version 2.59.3},
   url = {https://github.com/pik-piam/mrvalidation},
+  doi = {10.5281/zenodo.4317826},
 }
 ```