yield validation for fallow implementation

.buildlibrary

@@ -1,4 +1,4 @@
-ValidationKey: '49929037'
+ValidationKey: '50106580'
 AutocreateReadme: yes
 AcceptedWarnings:
 - 'Warning: package ''.*'' was built under R version'

CITATION.cff

@@ -2,7 +2,7 @@ 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: 2.53.1
+version: 2.54.0
 date-released: '2024-01-05'
 abstract: Package contains routines to prepare data for validation exercises.
 authors:

DESCRIPTION

@@ -1,7 +1,7 @@
 Type: Package
 Package: mrvalidation
 Title: madrat data preparation for validation purposes
-Version: 2.53.1
+Version: 2.54.0
 Date: 2024-01-05
 Authors@R: c(
     person("Benjamin Leon", "Bodirsky", , "[email protected]", role = c("aut", "cre")),

R/calcValidYield.R

@@ -101,21 +101,93 @@ calcValidYield  <-  function(datasource = "FAO", future = NULL) {
     scenario    <- "historical"
     description <- "CalcValidYield calculates the historical yield from FAO database."
 
+  } else if (datasource == "Ostberg2023_FAO_LUH2v2") {
+
+    if (!is.null(future)) stop("Future options is not available for source type 'FAO'.")
+
+    past <- findset("past")
+
+    # Calculate areas of individual crops and pasture
+    croparea <- calcOutput("CropareaLandInG", aggregate = FALSE)
+    pastarea  <-  setNames(calcOutput("LanduseInitialisation", aggregate = FALSE)[, , "past"],
+                           "pasture")
+    area <- mbind(croparea[, getYears(pastarea), ], pastarea)
+    area <- summationhelper(reporthelper(area,
+                                         level_zero_name = "Productivity|Yield by phyiscal area"))
+
+    # Calculate production
+    histproduction <- calcOutput("FAOmassbalance", aggregate = FALSE)
+    # extract DryMatter(dm) from production data
+    # Extract Production from subsetted production data containing only DryMatter(dm)
+    histproduction  <-  collapseNames(histproduction[, , "dm"][, , "production"])
+
+    # Figure out which commodities are common and make sure that production and area has same commodity names
+    kcr <- findset("kcr")
+    cropproduction  <-  histproduction[, , kcr]
+    pastproduction  <-  histproduction[, , "pasture"]
+    production <- mbind(cropproduction, pastproduction)
+
+    # Calculate Yields
+    production <- summationhelper(reporthelper(production,
+                                               level_zero_name = "Productivity|Yield by phyiscal area"))
+    yield      <-  production / area
+
+    # Check for NaN values
+    indexNaN  <-  which(is.nan(yield))
+    # Change NaN to 0
+    yield[is.nan(yield)] <- 0
+    if (length(indexNaN) > 0) {
+      vcat(verbosity = 2, "NaN values were found in the calculated yields ---> NaN values set to 0")
+    } else if (length(indexNaN) == 0) {
+      vcat(verbosity = 2, paste0("No NaN values detected in calculated yields. ",
+                                 "Yields for area reported as 0 are converted to 0."))
+    }
+
+    # Check for infinite values - Production reported but on 0 area
+    infindex  <-  which(is.infinite(yield)) # Lots of inf values. Being too diplomatic FAO aren't we!!
+    # Change inf to 0
+    yield[is.infinite(yield)] <- 0
+    if (length(infindex) > 0) {
+      vcat(verbosity = 2, "inf values were found in the calculated yields ---> inf values set to 0")
+    } else if (length(infindex) == 0) {
+      vcat(verbosity = 2, "No inf values found in the calculated yields")
+    }
+
+    ## Additional checks required because we are reporting insanely high yields
+    ## Check which(yield>200,arr.ind = TRUE)
+    ## looks like Vatican are the best producers of oil
+
+    ## We decided to set these outliers to 0
+    # look for the Region names which are outliers
+    region   <- rownames(which(yield > 200, arr.ind = TRUE))
+    # look for the Years where reporting is flawed
+    year     <- which(yield > 200, arr.ind = TRUE)[, 2]
+    # look for the scenario.model.Variable where reporting is flawed
+    variable <- which(yield > 200, arr.ind = TRUE)[, 3]
+
+    ## Now do the operation of our magpie object
+    yield[region, year, variable]  <-  0
+    vcat(verbosity = 2, paste0("Yields>200 ton/ha were converted to 0 ",
+                               "when area and production values were ambiguous"))
+
+    scenario    <- "historical"
+    description <- "FAO massbalance yields divided by physical area excluding fallow from Ostberg"
+
   } else if (datasource == "calibratedLPJmL") {
 
     irrigation <- FALSE # can be made function argument if needed
     yieldLPJmLgrid <- calcOutput("ValidGridYields", datasource = "calibratedLPJmL",
-                                  future = future, aggregate = FALSE)
+                                 future = future, aggregate = FALSE)
     areaMAGgrid    <- setYears(calcOutput("ValidGridCroparea", aggregate = FALSE)[, "y2010", ], NULL)
-    
+
     cell2iso <- data.frame(cell = getItems(yieldLPJmLgrid, 1, full = TRUE),
                            iso = getItems(yieldLPJmLgrid,
                                           if (dimExists("iso", yieldLPJmLgrid)) "iso" else 1.1, full = TRUE))
 
     yield <- toolAggregate(yieldLPJmLgrid, weight = areaMAGgrid, rel = cell2iso,
                            from = "celliso", to = "iso", dim = 1)
     area <- toolAggregate(areaMAGgrid, weight = NULL, rel = cell2iso,
-                           from = "celliso", to = "iso", dim = 1)
+                          from = "celliso", to = "iso", dim = 1)
 
 
     rm(yieldLPJmLgrid, areaMAGgrid)

R/fullVALIDATION.R

@@ -265,6 +265,8 @@ fullVALIDATION <- function(rev = 0.1) {
 
   # Yield
   calcOutput(type = "ValidYield", datasource = "FAO", aggregate = "REG+GLO", file = valfile, append = TRUE, try = TRUE)
+  calcOutput(type = "ValidYield", datasource = "Ostberg2023_FAO_LUH2v2",
+             aggregate = "REG+GLO", file = valfile, append = TRUE, try = TRUE)
 
   # Productivity
   calcOutput(type = "ValidTau", aggregate = "REG+GLO", file = valfile, append = TRUE, try = TRUE)

README.md

@@ -1,6 +1,6 @@
 # madrat data preparation for validation purposes
 
-R package **mrvalidation**, version **2.53.1**
+R package **mrvalidation**, version **2.54.0**
 
 [![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 (URL: https://doi.org/10.5281/zenodo.4317826), R package version 2.53.1, <URL: 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 (URL: https://doi.org/10.5281/zenodo.4317826), R package version 2.54.0, <URL: https://github.com/pik-piam/mrvalidation>.
 
 A BibTeX entry for LaTeX users is
 
@@ -48,7 +48,7 @@ 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 2.53.1},
+  note = {R package version 2.54.0},
   doi = {10.5281/zenodo.4317826},
   url = {https://github.com/pik-piam/mrvalidation},
 }