Update gh action + document with roxygen2 + replace T -> TRUE, F by FALSE to satisfy R CMD CHECK

.github/workflows/R-CMD-check.yaml

@@ -1,16 +1,10 @@
-# For help debugging build failures open an issue on the RStudio community with the 'github-actions' tag.
-# https://community.rstudio.com/new-topic?category=Package%20development&tags=github-actions
+# Workflow derived from https://github.com/r-lib/actions/tree/v2/examples
+# Need help debugging build failures? Start at https://github.com/r-lib/actions#where-to-find-help
 on:
   push:
-    branches:
-      - main
-      - master
-      - GitAction
-
+    branches: [main, master, GitAction]
   pull_request:
-    branches:
-      - main
-      - master
+    branches: [main, master]
 
 name: R-CMD-check
 
@@ -24,85 +18,44 @@ jobs:
       fail-fast: false
       matrix:
         config:
+          - {os: macos-latest,   r: 'release'}
           - {os: windows-latest, r: 'release'}
-          - {os: windows-latest, r: 'release'}
-          - {os: windows-latest, r: 'oldrel'}
-
-          # - {os: macOS-latest,   r: 'devel'}
-          - {os: macOS-latest,   r: 'release'}
-
-          - {os: ubuntu-20.04, r: 'release', rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
-          - {os: ubuntu-20.04, r: 'devel', rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
+          - {os: windows-latest, r: 'devel'}
+          - {os: ubuntu-latest,   r: 'devel', http-user-agent: 'release'}
+          - {os: ubuntu-latest,   r: 'release'}
+          - {os: ubuntu-latest,   r: 'oldrel-1'}
 
     env:
-      R_REMOTES_NO_ERRORS_FROM_WARNINGS: true
-      RSPM: ${{ matrix.config.rspm }}
       GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
+      R_KEEP_PKG_SOURCE: yes
 
     steps:
-
-      - uses: actions/checkout@v3
-
-      - uses: r-lib/actions/setup-r@v2
-        with:
-          r-version: ${{ matrix.config.r }}
+      - uses: actions/checkout@v4
 
       - uses: r-lib/actions/setup-pandoc@v2
-      
+
       - uses: r-lib/actions/setup-tinytex@v2
       - run: tlmgr --version
 
-      - name: Query dependencies
-        run: |
-          setwd("DHARMa")
-          install.packages('remotes')
-          saveRDS(remotes::dev_package_deps(dependencies = TRUE), "../.github/depends.Rds", version = 2)
-          writeLines(sprintf("R-%i.%i", getRversion()$major, getRversion()$minor), "../.github/R-version")
-        shell: Rscript {0}
-
-      - name: Cache R packages 
-        if: runner.os != 'Windows'
-        uses: actions/cache@v2
+      - uses: r-lib/actions/setup-r@v2
         with:
-          path: ${{ env.R_LIBS_USER }}
-          key: ${{ runner.os }}-${{ hashFiles('.github/R-version') }}-1-${{ hashFiles('.github/depends.Rds') }}
-          restore-keys: ${{ runner.os }}-${{ hashFiles('.github/R-version') }}-1-
-
-      - name: Install system dependencies
-        if: runner.os == 'Linux'
-        run: |
-          cd DHARMa
-          while read -r cmd
-          do
-            eval sudo $cmd
-          done < <(Rscript -e 'writeLines(remotes::system_requirements("ubuntu", "20.04"))')
+          r-version: ${{ matrix.config.r }}
+          http-user-agent: ${{ matrix.config.http-user-agent }}
+          use-public-rspm: true
 
-      - name: Install dependencies
-        run: |
-          setwd("DHARMa")
-          remotes::install_deps(dependencies = TRUE)
-          remotes::install_cran("rcmdcheck")
-        shell: Rscript {0}
-
-      - name: Check_II
-        env:
-          _R_CHECK_CRAN_INCOMING_REMOTE_: false
-          CI: true
-        run: |
-          rcmdcheck::rcmdcheck("DHARMa", args = c("--no-multiarch", "--no-manual"), error_on = "warning", check_dir = "check")
-        shell: Rscript {0}
-
-      - name: Check
-        env:
-          _R_CHECK_CRAN_INCOMING_REMOTE_: false
-          CI: true
-        run: |
-          rcmdcheck::rcmdcheck("DHARMa", args = c("--no-manual", "--as-cran"), error_on = "warning", check_dir = "check")
-        shell: Rscript {0}
+      - uses: r-lib/actions/setup-r-dependencies@v2
+        with:
+          extra-packages: any::rcmdcheck
+          needs: check
+          working-directory: DHARMa
+      # second check with different rcmdcheck arguments.
+      - uses: r-lib/actions/check-r-package@v2
+        with:
+          upload-snapshots: true
+          working-directory: DHARMa
+          args: 'c("--no-multiarch", "--no-manual")'
 
-      - name: Upload check results
-        if: failure()
-        uses: actions/upload-artifact@main
+      - uses: r-lib/actions/check-r-package@v2
         with:
-          name: ${{ runner.os }}-r${{ matrix.config.r }}-results
-          path: check
+          upload-snapshots: true
+          working-directory: DHARMa

DHARMa/R/DHARMa.R

@@ -95,7 +95,7 @@ outliers <- function(object, lowerQuantile = 0, upperQuantile = 1, return = c("i
 #' @note Either scaled residuals or (simulatedResponse AND observed response) have to be provided
 #' @example inst/examples/createDharmaHelp.R
 #' @export
-createDHARMa <- function(simulatedResponse , observedResponse , fittedPredictedResponse = NULL, integerResponse = F, seed = 123,  method = c("PIT", "traditional"), rotation = NULL){
+createDHARMa <- function(simulatedResponse , observedResponse , fittedPredictedResponse = NULL, integerResponse = FALSE, seed = 123,  method = c("PIT", "traditional"), rotation = NULL){
 
   randomState <-getRandomState(seed)
   on.exit({randomState$restoreCurrent()})
@@ -142,7 +142,7 @@ createDHARMa <- function(simulatedResponse , observedResponse , fittedPredictedR
 #' @return an object of class DHARMa
 #' @keywords internal
 ensureDHARMa <- function(simulationOutput,
-                         convert = F){
+                         convert = FALSE){
 
   if(inherits(simulationOutput, "DHARMa")){
     return(simulationOutput)
@@ -152,8 +152,8 @@ ensureDHARMa <- function(simulationOutput,
     else {
 
       if (class(simulationOutput)[1] %in% getPossibleModels()){
-        if (convert == "Model" | convert == T) return(simulateResiduals(simulationOutput))
-      } else if(is.vector(simulationOutput, mode = "numeric") & convert == T) {
+        if (convert == "Model" | convert == TRUE) return(simulateResiduals(simulationOutput))
+      } else if(is.vector(simulationOutput, mode = "numeric") & convert == TRUE) {
         out = list()
         out$scaledResiduals = simulationOutput
         out$nObs = length(out$scaledResiduals)

DHARMa/R/createData.R

@@ -20,7 +20,7 @@
 #' @param hasNA should an NA be added to the environmental predictor (for test purposes)
 #' @export
 #' @example /inst/examples/createDataHelp.R
-createData <- function(sampleSize = 100, intercept = 0, fixedEffects = 1, quadraticFixedEffects = NULL, numGroups = 10, randomEffectVariance = 1, overdispersion = 0, family = poisson(), scale = 1, cor = 0, roundPoissonVariance = NULL,  pZeroInflation = 0, binomialTrials = 1, temporalAutocorrelation = 0, spatialAutocorrelation =0, factorResponse = F, replicates=1, hasNA = F){
+createData <- function(sampleSize = 100, intercept = 0, fixedEffects = 1, quadraticFixedEffects = NULL, numGroups = 10, randomEffectVariance = 1, overdispersion = 0, family = poisson(), scale = 1, cor = 0, roundPoissonVariance = NULL,  pZeroInflation = 0, binomialTrials = 1, temporalAutocorrelation = 0, spatialAutocorrelation =0, factorResponse = FALSE, replicates=1, hasNA = FALSE){
 
   nPredictors = length(fixedEffects)
 

DHARMa/R/plots.R

@@ -4,7 +4,7 @@
 #' 
 #' @param x an object of class DHARMa with simulated residuals created by \code{\link{simulateResiduals}}
 #' @param ... further options for \code{\link{plotResiduals}}. Consider in particular parameters quantreg, rank and asFactor. xlab, ylab and main cannot be changed when using plot.DHARMa, but can be changed when using plotResiduals.
-#' @param title The title for both panels (plotted via mtext, outer = T)
+#' @param title The title for both panels (plotted via mtext, outer = TRUE)
 #' 
 #' @details The function creates a plot with two panels. The left panel is a uniform qq plot (calling \code{\link{plotQQunif}}), and the right panel shows residuals against predicted values (calling \code{\link{plotResiduals}}), with outliers highlighted in red. 
 #' 
@@ -31,7 +31,7 @@ plot.DHARMa <- function(x, title = "DHARMa residual", ...){
   plotQQunif(x)
   plotResiduals(x, ...)
 
-  mtext(title, outer = T)
+  mtext(title, outer = TRUE)
 }
 
 
@@ -57,7 +57,7 @@ hist.DHARMa <- function(x,
                         cex.main = 1,
                         ...){
 
-  x = ensureDHARMa(x, convert = T)
+  x = ensureDHARMa(x, convert = TRUE)
 
   val = x$scaledResiduals
   val[val == 0] = -0.01
@@ -97,7 +97,7 @@ plotSimulatedResiduals <- function(simulationOutput, ...){
 #' @seealso \code{\link{plotSimulatedResiduals}}, \code{\link{plotResiduals}}
 #' @example inst/examples/plotsHelp.R
 #' @export
-plotQQunif <- function(simulationOutput, testUniformity = T, testOutliers = T, testDispersion = T, ...){
+plotQQunif <- function(simulationOutput, testUniformity = TRUE, testOutliers = TRUE, testDispersion = TRUE, ...){
 
   a <- list(...)
   a$pch = checkDots("pch", 2, ...)
@@ -114,7 +114,7 @@ plotQQunif <- function(simulationOutput, testUniformity = T, testOutliers = T, t
   do.call(gap::qqunif, append(list(simulationOutput$scaledResiduals), a))
 
   if(testUniformity == TRUE){
-    temp = testUniformity(simulationOutput, plot = F)
+    temp = testUniformity(simulationOutput, plot = FALSE)
     legend("topleft", 
            c(paste("KS test: p=", round(temp$p.value, digits = 5)), 
              paste("Deviation ", ifelse(temp$p.value < 0.05, "significant", "n.s."))), 
@@ -123,7 +123,7 @@ plotQQunif <- function(simulationOutput, testUniformity = T, testOutliers = T, t
   }
 
   if(testOutliers == TRUE){
-    temp = testOutliers(simulationOutput, plot = F)
+    temp = testOutliers(simulationOutput, plot = FALSE)
     legend("bottomright", 
            c(paste("Outlier test: p=", round(temp$p.value, digits = 5)), 
              paste("Deviation ", ifelse(temp$p.value < 0.05, "significant", "n.s."))),
@@ -132,7 +132,7 @@ plotQQunif <- function(simulationOutput, testUniformity = T, testOutliers = T, t
   }
 
   if(testDispersion == TRUE){
-    temp = testDispersion(simulationOutput, plot = F)
+    temp = testDispersion(simulationOutput, plot = FALSE)
     legend("center", 
            c(paste("Dispersion test: p=", round(temp$p.value, digits = 5)), 
              paste("Deviation ", ifelse(temp$p.value < 0.05, "significant", "n.s."))), 
@@ -175,7 +175,7 @@ plotQQunif <- function(simulationOutput, testUniformity = T, testOutliers = T, t
 #' @seealso \code{\link{plotQQunif}}, \code{\link{testQuantiles}}, \code{\link{testOutliers}}
 #' @example inst/examples/plotsHelp.R
 #' @export
-plotResiduals <- function(simulationOutput, form = NULL, quantreg = NULL, rank = T, asFactor = NULL, smoothScatter = NULL, quantiles = c(0.25, 0.5, 0.75), absoluteDeviation = FALSE, ...){
+plotResiduals <- function(simulationOutput, form = NULL, quantreg = NULL, rank = TRUE, asFactor = NULL, smoothScatter = NULL, quantiles = c(0.25, 0.5, 0.75), absoluteDeviation = FALSE, ...){
 
 
   ##### Checks #####
@@ -185,12 +185,12 @@ plotResiduals <- function(simulationOutput, form = NULL, quantreg = NULL, rank =
   a$ylab = checkDots("ylab", yAxis , ...)
   a$xlab = checkDots("xlab", ifelse(is.null(form), "Model predictions", 
                                     gsub(".*[$]","",deparse(substitute(form)))), ...)
-  if(rank == T) a$xlab = paste(a$xlab, "(rank transformed)")
+  if(rank == TRUE) a$xlab = paste(a$xlab, "(rank transformed)")
 
-  simulationOutput = ensureDHARMa(simulationOutput, convert = T)
+  simulationOutput = ensureDHARMa(simulationOutput, convert = TRUE)
   res = simulationOutput$scaledResiduals
 
-  if(absoluteDeviation == T){
+  if(absoluteDeviation == TRUE){
     res = 2 * abs(res - 0.5)
   }
 
@@ -202,7 +202,7 @@ plotResiduals <- function(simulationOutput, form = NULL, quantreg = NULL, rank =
 
   if(!is.factor(pred)){
 
-    if (rank == T){
+    if (rank == TRUE){
       pred = rank(pred, ties.method = "average")
       pred = pred / max(pred)
       a$xlim = checkDots("xlim", c(0,1), ...)
@@ -256,16 +256,16 @@ plotResiduals <- function(simulationOutput, form = NULL, quantreg = NULL, rank =
   out = NULL
 
   if(is.numeric(pred)){
-    if(quantreg == F){
+    if(quantreg == FALSE){
       title(main = main, cex.main = 1)
       abline(h = quantiles, col = "black", lwd = 0.5, lty = 2)
       try({
         lines(smooth.spline(pred, res, df = 10), lty = 2, lwd = 2, col = "red")
         abline(h = 0.5, col = "red", lwd = 2)
-      }, silent = T)
+      }, silent = TRUE)
     }else{
 
-      out = testQuantiles(res, pred, quantiles = quantiles, plot = F)
+      out = testQuantiles(res, pred, quantiles = quantiles, plot = FALSE)
 
 
       if(any(out$pvals < 0.05, na.rm = TRUE)){
@@ -293,7 +293,7 @@ plotResiduals <- function(simulationOutput, form = NULL, quantreg = NULL, rank =
         abline(h = quantiles[i], col = lineCol, lwd = 0.5, lty = 2)
         polygon(c(out$predictions$pred, rev(out$predictions$pred)),
                 c(out$predictions[,2*i] - out$predictions[,2*i+1], rev(out$predictions[,2*i] + out$predictions[,2*i+1])),
-                col = "#00000020", border = F)
+                col = "#00000020", border = FALSE)
         lines(out$predictions$pred, out$predictions[,2*i], col = lineCol, lwd = 2)
       }
 
@@ -358,15 +358,15 @@ plotConventionalResiduals <- function(fittedModel){
   plot(predict(fittedModel), resid(fittedModel, type = "deviance"), main = "Deviance" , ylab = "Residual", xlab = "Predicted")
   plot(predict(fittedModel), resid(fittedModel, type = "pearson") , main = "Pearson", ylab = "Residual", xlab = "Predicted")
   plot(predict(fittedModel), resid(fittedModel, type = "response") , main = "Raw residuals" , ylab = "Residual", xlab = "Predicted")
-  mtext("Conventional residual plots", outer = T)
+  mtext("Conventional residual plots", outer = TRUE)
 }
 
 
 
 
 #
 #
-# if(quantreg == F){
+# if(quantreg == FALSE){
 #
 #   lines(smooth.spline(simulationOutput$fittedPredictedResponse, simulationOutput$scaledResiduals, df = 10), lty = 2, lwd = 2, col = "red")
 #

DHARMa/R/random.R

@@ -22,7 +22,7 @@ getRandomState <- function(seed = NULL){
 
   current = mget(".Random.seed", envir = .GlobalEnv, ifnotfound = list(NULL))[[1]]
 
-  if(!is.null(seed) && is.logical(seed) && seed == F){
+  if(!is.null(seed) && is.logical(seed) && seed == FALSE){
     restoreCurrent <- function(){}    
   }else{
     restoreCurrent <- function(){