Merge pull request #91 from tonnrueter/master

Fix empty canvas issues in plotPercentiles

.buildlibrary

@@ -1,4 +1,4 @@
-ValidationKey: '29421782'
+ValidationKey: '29444544'
 AcceptedWarnings:
 - 'Warning: package ''.*'' was built under R version'
 - 'Warning: namespace ''.*'' is not available and has been replaced'

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: 'mip: Comparison of multi-model runs'
-version: 0.148.7
-date-released: '2024-03-04'
+version: 0.148.8
+date-released: '2024-03-06'
 abstract: Package contains generic functions to produce comparison plots of multi-model
   runs.
 authors:

DESCRIPTION

@@ -1,8 +1,8 @@
 Type: Package
 Package: mip
 Title: Comparison of multi-model runs
-Version: 0.148.7
-Date: 2024-03-04
+Version: 0.148.8
+Date: 2024-03-06
 Authors@R: c(
     person("David", "Klein", , "[email protected]", role = c("aut", "cre")),
     person("Jan Philipp", "Dietrich", , "[email protected]", role = "aut"),

NAMESPACE

@@ -195,6 +195,7 @@ importFrom(stats,na.omit)
 importFrom(stats,reshape)
 importFrom(stats,runif)
 importFrom(stringr,str_extract)
+importFrom(tidyr,all_of)
 importFrom(tidyr,crossing)
 importFrom(tidyr,drop_na)
 importFrom(tidyr,pivot_wider)

R/plotPercentiles.R

@@ -27,25 +27,31 @@
 #' }
 #' @section Example Plot:
 #' \if{html}{\figure{plotPercentiles1.png}{Atmospheric CO2 concentrations for all scenarios available in the data}}
-#' @importFrom dplyr filter mutate vars
+#' @importFrom dplyr filter mutate vars select
 #' @importFrom reshape2 melt
 #' @importFrom stringr str_extract
-#' @importFrom tidyr pivot_wider
+#' @importFrom tidyr pivot_wider all_of
 #' @importFrom ggplot2 ggplot geom_line geom_ribbon facet_wrap facet_grid theme ylab
 #' @export
 plotPercentiles <- function(df, scenarios = NULL, variables = NULL) {
-
+  # Dropped "model" from Necessary columns
+  necessaryCols <- c("scenario", "region", "variable", "unit", "period", "value")
   # In the quitte data frame all percentiles are given as individual variables. Manipulate input data frame such that
-  # all percentiles of a given quantity are transformed to individual columns. Variable names in the quitte data frame
-  # follow the format "Any|Variable|5.0th Percentile". The regular expressions below divide the variable name into the
-  # prefix and the percentile specifier
+  # all percentiles of a given quantity are transformed to individual columns
   data <- df %>%
+    # Drop NA values
     as.quitte(na.rm = TRUE) %>%
+    # Only use necessary columns. The .data-prefix in col names was deprecated in tidyselect since v1.2.0.
+    select(all_of(necessaryCols)) %>%
+    # Variable names in the quitte data frame follow the format "Any|Variable|5.0th Percentile". The regular 
+    # expressions below divide the variable name into the prefix and the percentile specifier
     mutate(
       "percentile" = stringr::str_extract(.data$variable, "[^\\|]+?$"),
       "variable"   = gsub("\\|[^\\|]+$", "", .data$variable)
     ) %>%
+    # Remove all non-percentile variables
     filter(grepl(" Percentile$", .data$percentile)) %>%
+    # Pivot data such that percentiles are transformed to individual columns
     pivot_wider(
       names_from = "percentile",
       values_from = "value"

README.md

@@ -1,6 +1,6 @@
 # Comparison of multi-model runs
 
-R package **mip**, version **0.148.7**
+R package **mip**, version **0.148.8**
 
 [![CRAN status](https://www.r-pkg.org/badges/version/mip)](https://cran.r-project.org/package=mip) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.1158586.svg)](https://doi.org/10.5281/zenodo.1158586) [![R build status](https://github.com/pik-piam/mip/workflows/check/badge.svg)](https://github.com/pik-piam/mip/actions) [![codecov](https://codecov.io/gh/pik-piam/mip/branch/master/graph/badge.svg)](https://app.codecov.io/gh/pik-piam/mip) [![r-universe](https://pik-piam.r-universe.dev/badges/mip)](https://pik-piam.r-universe.dev/builds)
 
@@ -47,7 +47,7 @@ In case of questions / problems please contact David Klein <[email protected]
 
 To cite package **mip** in publications use:
 
-Klein D, Dietrich J, Baumstark L, Humpenoeder F, Stevanovic M, Wirth S, Führlich P, Richters O, Rüter T (2024). _mip: Comparison of multi-model runs_. doi:10.5281/zenodo.1158586 <https://doi.org/10.5281/zenodo.1158586>, R package version 0.148.7, <https://github.com/pik-piam/mip>.
+Klein D, Dietrich J, Baumstark L, Humpenoeder F, Stevanovic M, Wirth S, Führlich P, Richters O, Rüter T (2024). _mip: Comparison of multi-model runs_. doi: 10.5281/zenodo.1158586 (URL: https://doi.org/10.5281/zenodo.1158586), R package version 0.148.8, <URL: https://github.com/pik-piam/mip>.
 
 A BibTeX entry for LaTeX users is
 
@@ -56,7 +56,7 @@ A BibTeX entry for LaTeX users is
   title = {mip: Comparison of multi-model runs},
   author = {David Klein and Jan Philipp Dietrich and Lavinia Baumstark and Florian Humpenoeder and Miodrag Stevanovic and Stephen Wirth and Pascal Führlich and Oliver Richters and Tonn Rüter},
   year = {2024},
-  note = {R package version 0.148.7},
+  note = {R package version 0.148.8},
   doi = {10.5281/zenodo.1158586},
   url = {https://github.com/pik-piam/mip},
 }