Current v6.3.5 dev integrated with v7.0-dev #629

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Merged

StuartWheater merged 39 commits into v7.0-dev from v6.3.5-dev

Nov 14, 2025

.Rbuildignore

            
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    @@ -17,8 +17,8 @@
  
    ^R/secure.global.ranking.md$

    ^_pkgdown\.yml$

    ^docs$

    ^dsBase_6.3.4.tar.gz$

    ^dsBase_6.3.4-permissive.tar.gz$

    ^dsBase_6.3.5.tar.gz$

    ^dsBase_6.3.5-permissive.tar.gz$

    ^dsDanger_6.3.4.tar.gz$

    ^\.circleci$

    ^\.circleci/config\.yml$

DESCRIPTION

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@@ -1,6 +1,6 @@
     Package: dsBaseClient
     Title: 'DataSHIELD' Client Side Base Functions
-    Version: 6.3.4
+    Version: 6.3.5-9000
     Description: Base 'DataSHIELD' functions for the client 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
@@ Expand Down Expand Up / @@ -36,10 +36,6 @@ Authors@R: c(person(given = "Paul", @@
                         family = "Avraam",
                         role = c("aut"),
                         comment = c(ORCID = "0000-0001-8908-2441")),
-                 person(given = "Demetris",
-                        family = "Avraam",
-                        role = c("aut"),
-                        comment = c(ORCID = "0000-0001-8908-2441")),
                  person(given = "Yannick",
                         family = "Marcon",
                         role = c("aut"),
@@ Expand Down @@

NAMESPACE

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+Diff line change
@@ Expand Up / @@ -73,6 +73,7 @@ export(ds.matrixDimnames) @@
     export(ds.matrixInvert)
     export(ds.matrixMult)
     export(ds.matrixTranspose)
+    export(ds.mdPattern)
     export(ds.mean)
     export(ds.meanByClass)
     export(ds.meanSdGp)
@@ Expand Down @@

R/ds.asFactor.R

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@@ Expand Up / @@ -48,7 +48,7 @@ @@
     #' \code{baseline.level = 1} and \code{forced.factor.levels = c(1,2,3,4,5)}.
     #' The input vector is converted to the following matrix of dummy variables:
     #'
-    #' \tabular{rrrrr}{
+    #' \tabular{rrrr}{
     #'   \strong{DV2} \tab \strong{DV3} \tab \strong{DV4} \tab \strong{DV5} \cr
     #'     0   \tab  0  \tab  0  \tab  0\cr
     #'     1   \tab  0  \tab  0  \tab  0\cr
@@ Expand Down @@

R/ds.colnames.R

            
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    @@ -1,51 +1,51 @@
  
    #'

    #' @title Produces column names of the R object in the server-side

    #' @description Retrieves column names of an R object on the server-side.  

    #' @description Retrieves column names of an R object on the server-side.

    #' This function is similar to R function \code{colnames}.

    #' @details The input is restricted to the object of type \code{data.frame} or \code{matrix}. 

    #' 

    #' @details The input is restricted to the object of type \code{data.frame} or \code{matrix}.

    #'

    #' Server function called: \code{colnamesDS}

    #' @param x a character string providing the name of the input data frame or matrix.

    #' @param datasources a list of \code{\link[DSI]{DSConnection-class}} objects obtained after login. 

    #' @param datasources a list of \code{\link[DSI]{DSConnection-class}} objects obtained after login.

    #' If the \code{datasources} argument is not specified

    #' the default set of connections will be used: see \code{\link[DSI]{datashield.connections_default}}.

    #' @return \code{ds.colnames} returns the column names of 

    #' the specified server-side data frame or matrix. 

    #' @return \code{ds.colnames} returns the column names of

    #' the specified server-side data frame or matrix.

    #' @author DataSHIELD Development Team

    #' @seealso \code{\link{ds.dim}} to obtain the dimensions of a matrix or a data frame.

    #' @examples 

    #' @examples

    #' \dontrun{

    #' 

    #'

    #'   ## Version 6, for version 5 see the Wiki

    #'   # Connecting to the Opal servers

    #' 

    #'

    #'   require('DSI')

    #'   require('DSOpal')

    #'   require('dsBaseClient')

    #' 

    #'

    #'   builder <- DSI::newDSLoginBuilder()

    #'   builder$append(server = "study1", 

    #'                  url = "http://192.168.56.100:8080/", 

    #'                  user = "administrator", password = "datashield_test&", 

    #'   builder$append(server = "study1",

    #'                  url = "http://192.168.56.100:8080/",

    #'                  user = "administrator", password = "datashield_test&",

    #'                  table = "CNSIM.CNSIM1", driver = "OpalDriver")

    #'   builder$append(server = "study2", 

    #'                  url = "http://192.168.56.100:8080/", 

    #'                  user = "administrator", password = "datashield_test&", 

    #'   builder$append(server = "study2",

    #'                  url = "http://192.168.56.100:8080/",

    #'                  user = "administrator", password = "datashield_test&",

    #'                  table = "CNSIM.CNSIM2", driver = "OpalDriver")

    #'   builder$append(server = "study3",

    #'                  url = "http://192.168.56.100:8080/", 

    #'                  user = "administrator", password = "datashield_test&", 

    #'                  url = "http://192.168.56.100:8080/",

    #'                  user = "administrator", password = "datashield_test&",

    #'                  table = "CNSIM.CNSIM3", driver = "OpalDriver")

    #'   logindata <- builder$build()

    #'   

    #'

    #'   # Log onto the remote Opal training servers

    #'   connections <- DSI::datashield.login(logins = logindata, assign = TRUE, symbol = "D") 

    #' 

    #'   connections <- DSI::datashield.login(logins = logindata, assign = TRUE, symbol = "D")

    #'

    #'   # Getting column names of the R objects stored in the server-side

    #'   ds.colnames(x = "D",

    #'               datasources = connections[1]) #only the first server ("study1") is used

    #'   # Clear the Datashield R sessions and logout

    #'   datashield.logout(connections) 

    #'   datashield.logout(connections)

    #' }

    #' @export

    #'

    @@ -65,17 +65,6 @@ ds.colnames <- function(x=NULL, datasources=NULL) {
  
        stop("Please provide the name of a data.frame or matrix!", call.=FALSE)

      }

      # check if the input object(s) is(are) defined in all the studies

      defined <- isDefined(datasources, x)

      # call the internal function that checks the input object is of the same class in all studies.

      typ <- checkClass(datasources, x)

      # if the input object is not a matrix or a dataframe stop

      if(!('data.frame' %in% typ) & !('matrix' %in% typ)){

        stop("The input vector must be of type 'data.frame' or a 'matrix'!", call.=FALSE)

      }

      cally <- call("colnamesDS", x)

      column_names <- DSI::datashield.aggregate(datasources, cally)

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