V6.3.3 dev - CRAN submission

.github/.gitignore

@@ -0,0 +1 @@
+*.html

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

@@ -0,0 +1,51 @@
+# 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]
+  pull_request:
+
+name: R-CMD-check.yaml
+
+permissions: read-all
+
+jobs:
+  R-CMD-check:
+    runs-on: ${{ matrix.config.os }}
+
+    name: ${{ matrix.config.os }} (${{ matrix.config.r }})
+
+    strategy:
+      fail-fast: false
+      matrix:
+        config:
+          - {os: macos-latest,   r: 'release'}
+          - {os: windows-latest, r: 'release'}
+          - {os: ubuntu-latest,   r: 'devel', http-user-agent: 'release'}
+          - {os: ubuntu-latest,   r: 'release'}
+          - {os: ubuntu-latest,   r: 'oldrel-1'}
+
+    env:
+      GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
+      R_KEEP_PKG_SOURCE: yes
+
+    steps:
+      - uses: actions/checkout@v4
+
+      - uses: r-lib/actions/setup-pandoc@v2
+
+      - uses: r-lib/actions/setup-r@v2
+        with:
+          r-version: ${{ matrix.config.r }}
+          http-user-agent: ${{ matrix.config.http-user-agent }}
+          use-public-rspm: true
+
+      - uses: r-lib/actions/setup-r-dependencies@v2
+        with:
+          extra-packages: any::rcmdcheck
+          needs: check
+
+      - uses: r-lib/actions/check-r-package@v2
+        with:
+          upload-snapshots: true
+          build_args: 'c("--no-manual", "--as-cran", "--compact-vignettes=gs+qpdf")'

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: dsBase
-Title: DataSHIELD Server Site Base Functions
-Description: Base DataSHIELD functions for the server side. DataSHIELD is a software package which allows
-    you to do non-disclosive federated analysis on sensitive data. DataSHIELD analytic functions have
+Title: 'DataSHIELD' Server Site Base Functions
+Description: Base 'DataSHIELD' functions for the server side. 'DataSHIELD' is a software package which allows
+    you to do non-disclosive federated analysis on sensitive data. 'DataSHIELD' analytic functions have
     been designed to only share non disclosive summary statistics, with built in automated output
     checking based on statistical disclosure control. With data sites setting the threshold values for
     the automated output checks.
@@ -59,180 +59,5 @@ Imports:
     childsds
 Suggests:
     testthat
-AggregateMethods:
-    asFactorDS1,
-    asListDS,
-    aucDS,
-    boxPlotGGDS,
-    checkNegValueDS,
-    classDS,
-    colnamesDS,
-    corTestDS,
-    corDS,
-    covDS,
-    dataFrameSubsetDS1,
-    densityGridDS,
-    extractQuantilesDS1,
-    extractQuantilesDS2,
-    dimDS,
-    gamlssDS,
-    glmDS1,
-    glmDS2,
-    glmerSLMADS2,
-    glmPredictDS.ag,
-    glmSLMADS1,
-    glmSLMADS2,
-    glmSummaryDS.ag,
-    heatmapPlotDS,
-    hetcorDS,
-    histogramDS1,
-    histogramDS2,
-    isNaDS,
-    isValidDS,
-    kurtosisDS1,
-    kurtosisDS2,
-    lengthDS,
-    levelsDS,
-    lexisDS1,
-    listDisclosureSettingsDS,
-    lmerSLMADS2,
-    lsDS,
-    matrixDetDS1,
-    meanDS,
-    meanSdGpDS,
-    messageDS,
-    metadataDS,
-    miceDS,
-    minMaxRandDS,
-    namesDS,
-    numNaDS,
-    quantileMeanDS,
-    rangeDS,
-    ranksSecureDS1,
-    ranksSecureDS3,
-    rmDS,
-    scatterPlotDS,
-    scoreVectDS,
-    setSeedDS,
-    skewnessDS1,
-    skewnessDS2,
-    table1DDS,
-    table2DDS,
-    tableDS,
-    tableDS2,
-    tapplyDS,
-    testObjExistsDS,
-    varDS,
-    exists=base::exists,
-    is.character=base::is.character,
-    is.factor=base::is.factor,
-    is.list=base::is.list,
-    is.null=base::is.null,
-    is.numeric=base::is.numeric,
-    NROW=base::NROW,
-    t.test=stats::t.test
-AssignMethods:
-    absDS,
-    asCharacterDS,
-    asDataMatrixDS,
-    asFactorDS2,
-    asFactorSimpleDS,
-    asIntegerDS,
-    asListDS,
-    asLogicalDS,
-    asMatrixDS,
-    asNumericDS,
-    blackBoxDS,
-    blackBoxRanksDS,
-    BooleDS,
-    boxPlotGG_data_TreatmentDS,
-    boxPlotGG_data_Treatment_numericDS,
-    bp_standardsDS,
-    cbindDS,
-    cDS,
-    changeRefGroupDS,
-    completeCasesDS,
-    dataFrameDS,
-    dataFrameFillDS,
-    dataFrameSortDS,
-    dataFrameSubsetDS2,
-    dmtC2SDS,
-    elsplineDS,
-    glmerSLMADS.assign,
-    glmPredictDS.as,
-    glmSLMADS.assign,
-    glmSummaryDS.as,
-    getWGSRDS,
-    igb_standardsDS,
-    listDS,
-    lexisDS2,
-    lexisDS3,
-    lmerSLMADS.assign,
-    lsplineDS,
-    matrixDetDS2,
-    matrixDiagDS,
-    matrixDimnamesDS,
-    matrixDS,
-    matrixInvertDS,
-    matrixMultDS,
-    matrixTransposeDS,
-    mergeDS,
-    nsDS,
-    qlsplineDS,
-    ranksSecureDS2,
-    ranksSecureDS4,
-    ranksSecureDS5,
-    rbindDS,
-    rBinomDS,
-    recodeLevelsDS,
-    recodeValuesDS,
-    repDS,
-    replaceNaDS,
-    reShapeDS,
-    rNormDS,
-    rowColCalcDS,
-    rPoisDS,
-    rUnifDS,
-    sampleDS,
-    seqDS,
-    sqrtDS,
-    subsetByClassDS,
-    subsetDS,
-    tableDS.assign,
-    tapplyDS.assign,
-    uniqueDS,
-    unListDS,
-    vectorDS,
-    as.character=base::as.character,
-    as.null=base::as.null,
-    as.numeric=base::as.numeric,
-    attach=base::attach,
-    c=dsBase::vectorDS,
-    complete.cases=stats::complete.cases,
-    list=base::list,
-    exp=base::exp,
-    log=base::log,
-    sqrt=base::sqrt,
-    abs=base::abs,
-    sin=base::sin,
-    cos=base::cos,
-    tan=base::tan,
-    asin=base::asin,
-    acos=base::acos,
-    atan=base::atan,
-    sum=base::sum,
-    unlist=base::unlist
-Options:
-    datashield.privacyLevel=5,
-    default.datashield.privacyControlLevel="banana",
-    default.nfilter.glm=0.33,
-    default.nfilter.kNN=3,
-    default.nfilter.string=80,
-    default.nfilter.subset=3,
-    default.nfilter.stringShort=20,
-    default.nfilter.tab=3,
-    default.nfilter.noise=0.25,
-    default.nfilter.levels.density=0.33,
-    default.nfilter.levels.max=40
 RoxygenNote: 7.3.2
 Encoding: UTF-8

R/BooleDS.R

@@ -18,9 +18,11 @@
 #' @param na.assign.text A character string taking values 'NA', '1' or '0'. If 'NA'
 #' then any NA values in the
 #' input vector remain as NAs in the output vector. If '1' or '0' NA values in the
-#' input vector are
-#' all converted to 1 or 0 respectively.#' @return the levels of the input variable.
+#' input vector are all converted to 1 or 0 respectively.
+#' 
 #' @author DataSHIELD Development Team
+#' 
+#' @return the levels of the input variable.
 #' @export
 #'
 BooleDS <- function(V1.name=NULL, V2.name=NULL, Boolean.operator.n=NULL, na.assign.text, numeric.output=TRUE){

R/absDS.R

@@ -6,21 +6,19 @@
 #' @param x a string character, the name of a numeric or integer vector
 #' @return the object specified by the \code{newobj} argument
 #' of \code{ds.abs} (or default name \code{abs.newobj})
-#' which is written to the serverside. The output object is of class numeric 
+#' which is written to the serverside. The output object is of class numeric
 #' or integer.
 #' @author Demetris Avraam for DataSHIELD Development Team
 #' @export
 #'
-absDS <- function(x){
-
-  x.var <- eval(parse(text=x), envir = parent.frame())
+absDS <- function(x) {
+  x.var <- eval(parse(text = x), envir = parent.frame())
 
   # compute the absolute values of x
   out <- abs(x.var)
-  
+
   # assign the outcome to the data servers
   return(out)
-
 }
 # ASSIGN FUNCTION
 # absDS

R/asCharacterDS.R

@@ -1,4 +1,4 @@
-#' 
+#'
 #' @title Coerces an R object into class character
 #' @description this function is based on the native R function \code{as.character}
 #' @details See help for function \code{as.character} in native R
@@ -11,14 +11,12 @@
 #' details see help on the clientside function \code{ds.asCharacter}
 #' @author Amadou Gaye, Paul Burton, Demetris Avraam for DataSHIELD Development Team
 #' @export
-#' 
-asCharacterDS <- function (x.name){
-
-  x<-eval(parse(text=x.name), envir = parent.frame())
+#'
+asCharacterDS <- function(x.name) {
+  x <- eval(parse(text = x.name), envir = parent.frame())
 
   output <- as.character(x)
   return(output)
-
 }
 # ASSIGN FUNCTION
 # asCharacterDS

R/asDataMatrixDS.R

@@ -16,15 +16,13 @@
 #' details see help on the clientside function \code{ds.asDataMatrix}
 #' @author Paul Burton for DataSHIELD Development Team
 #' @export
-asDataMatrixDS <- function (x.name){
-
-if(is.character(x.name)){
-	x<-eval(parse(text=x.name), envir = parent.frame())
-
-	}else{
-   studysideMessage<-"ERROR: x.name must be specified as a character string"
-   stop(studysideMessage, call. = FALSE)
-   }
+asDataMatrixDS <- function(x.name) {
+  if (is.character(x.name)) {
+    x <- eval(parse(text = x.name), envir = parent.frame())
+  } else {
+    studysideMessage <- "ERROR: x.name must be specified as a character string"
+    stop(studysideMessage, call. = FALSE)
+  }
 
   output <- data.matrix(x)
 

R/asFactorDS2.R

@@ -9,7 +9,7 @@
 #' @param all.unique.levels.transmit the levels that the variable will be transmitted to.
 #' @param fixed.dummy.vars a boolean that determines whether the new object will be represented as
 #' a vector or as a matrix of dummy variables indicating the factor level of each data point.
-#' If this argyment is set to FALSE (default) then the input variable is converted to a factor and
+#' If this argument is set to FALSE (default) then the input variable is converted to a factor and
 #' assigned as a vector. If is set to TRUE then the input variable is converted to a factor but
 #' assigned as a matrix of dummy variables.
 #' @param baseline.level a number indicating the baseline level to be used in the creation of the

R/blackBoxDS.R

@@ -65,7 +65,10 @@ blackBoxDS <- function(input.var.name=NULL,
   #nfilter.noise <- as.numeric(thr$nfilter.noise)
   #nfilter.levels <- as.numeric(thr$nfilter.levels)
   ########################################################
-
+
+  # back-up current .Random.seed and revert on.exit
+  old_seed <- .Random.seed
+  on.exit(.Random.seed <- old_seed, add = TRUE)
 
  input.var <- eval(parse(text=input.var.name), envir = parent.frame())
 
@@ -311,7 +314,7 @@ utils::head(rank.intermediate.value.matrix)
 utils::tail(rank.intermediate.value.matrix)
 
 
-cat("\nRANKS IN ALL COLUMNS ABOVE SHOULD BE THE SAME\n")
+message("\nRANKS IN ALL COLUMNS ABOVE SHOULD BE THE SAME\n")
 
 control.vector
 control.value
@@ -365,7 +368,7 @@ if(sum(round(rank(blackbox.output.df[,3])-rank(blackbox.output.df[,4]),2)==0)!=n
             of memory")
   stop(error.message, call. = FALSE)
 }else{
-  cat("\nPROCESSING SUCCESSFUL, ALL RANKS AGREE FOR ALL TRANSFORMATIONS\n\n")
+  message("\nPROCESSING SUCCESSFUL, ALL RANKS AGREE FOR ALL TRANSFORMATIONS\n\n")
 }
 
 

R/blackBoxRanksDS.R

@@ -61,6 +61,9 @@ blackBoxRanksDS <- function(input.var.name=NULL, shared.seedval){ #START FUNC
   #nfilter.levels <- as.numeric(thr$nfilter.levels)       
   ########################################################
 
+  # back-up current .Random.seed and revert on.exit
+  old_seed <- .Random.seed
+  on.exit(.Random.seed <- old_seed, add = TRUE)
 
 input.var <- eval(parse(text=input.var.name), envir = parent.frame())
 input.global.ranks<-input.var
@@ -189,7 +192,7 @@ colnames(rank.intermediate.value.matrix)<-c("input.global.ranks.orig","input.var
                                             1:6,"ID.seq.real.orig")
 
 
-cat("\nRANKS IN ALL COLUMNS ABOVE SHOULD BE THE SAME\n")
+message("\nRANKS IN ALL COLUMNS ABOVE SHOULD BE THE SAME\n")
 
 control.vector
 control.value
@@ -255,7 +258,7 @@ if(sum(round(rank(blackbox.ranks.df[,5])-rank(blackbox.ranks.df[,8]),2)==0)!=num
             of memory")
   stop(error.message, call. = FALSE)
 }else{
-  cat("\nPROCESSING SUCCESSFUL, ALL RANKS AGREE FOR ALL TRANSFORMATIONS\n\n")
+  message("\nPROCESSING SUCCESSFUL, ALL RANKS AGREE FOR ALL TRANSFORMATIONS\n\n")
 }