add the new ds.sqrt/sqrtDS function

Author: davraam

NAMESPACE

@@ -84,6 +84,7 @@ export(ds.seq)
 export(ds.setDefaultOpals)
 export(ds.setSeed)
 export(ds.skewness)
+export(ds.sqrt)
 export(ds.subset)
 export(ds.subsetByClass)
 export(ds.summary)

R/ds.sqrt.R

@@ -0,0 +1,116 @@
+#'
+#' @title Computes the square root values of a variable
+#' @description Computes the square root values for a specified numeric or integer vector. 
+#' This function is similar to R function \code{sqrt}.
+#' @details The function calls the server-side function \code{sqrtDS} that computes the 
+#' square root values of the elements of a numeric or integer vector and assigns a new vector 
+#' with those square root values on the server-side. The name of the new generated vector is 
+#' specified by the user through the argument \code{newobj}, otherwise is named by default to
+#' \code{sqrt.newobj}.
+#' @param x a character string providing the name of a numeric or an integer vector.
+#' @param newobj a character string that provides the name for the output variable
+#' that is stored on the data servers. Default name is set to \code{sqrt.newobj}. 
+#' @param datasources a list of \code{\link{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{datashield.connections_default}}.
+#' @return \code{ds.sqrt} assigns a vector for each study that includes the square root values of
+#' the input numeric or integer vector specified in the argument \code{x}. The created vectors
+#' are stored in the servers.
+#' @author Demetris Avraam for DataSHIELD Development Team
+#' @export
+#' @examples
+#' \dontrun{
+#'
+#'   # Connecting to the Opal servers
+#' 
+#'   require('DSI')
+#'   require('DSOpal')
+#'   require('dsBaseClient')
+#' 
+#'   builder <- DSI::newDSLoginBuilder()
+#'   builder$append(server = "study1", 
+#'                  url = "http://192.168.56.100:8080/", 
+#'                  user = "administrator", password = "datashield_test&", 
+#'                  table = "CNSIM.CNSIM1", driver = "OpalDriver")
+#'   builder$append(server = "study2", 
+#'                  url = "http://192.168.56.100:8080/", 
+#'                  user = "administrator", password = "datashield_test&", 
+#'                  table = "CNSIM.CNSIM2", driver = "OpalDriver")
+#'   builder$append(server = "study3",
+#'                  url = "http://192.168.56.100:8080/", 
+#'                  user = "administrator", password = "datashield_test&", 
+#'                  table = "CNSIM.CNSIM3", driver = "OpalDriver")
+#'                  
+#'   logindata <- builder$build()
+#'   
+#'   # Log onto the remote Opal training servers
+#'   connections <- DSI::datashield.login(logins = logindata, assign = TRUE, symbol = "D") 
+#'   
+#'   # Example 1: Get the square root of LAB_HDL variable
+#'   ds.sqrt(x='D$LAB_HDL', newobj='LAB_HDL.sqrt', datasources=connections)
+#'   # compare the mean of LAB_HDL and of LAB_HDL.sqrt
+#'   # Note here that the number of missing values is bigger in the LAB_HDL.sqrt 
+#    # vector, because the variable LAB_HDL includes negative values which
+#    # don't have real square roots and those values are returned as NAs.
+#'   ds.mean(x='D$LAB_HDL', datasources=connections)
+#'   ds.mean(x='LAB_HDL.sqrt', datasources=connections)
+#'
+#'   # Example 2: Generate a repeated vector of the squares of integers from 1 to 10
+#'   # and get their square roots
+#'   ds.make(toAssign='rep((1:10)^2, times=10)', newobj='squares.vector', datasources=connections)
+#'   ds.sqrt(x='squares.vector', newobj='sqrt.vector', datasources=connections)
+#'   # check the behavior of that operation by comparing the tables of squares.vector and sqrt.vector
+#'   ds.table(rvar='squares.vector')$output.list$TABLE_rvar.by.study_counts
+#'   ds.table(rvar='sqrt.vector')$output.list$TABLE_rvar.by.study_counts
+#'
+#'   # clear the Datashield R sessions and logout
+#'   datashield.logout(connections) 
+#'
+#' }
+#'
+ds.sqrt <- function(x=NULL, newobj=NULL, datasources=NULL){
+
+  # look for DS connections
+  if(is.null(datasources)){
+    datasources <- datashield.connections_find()
+  }
+
+  if(is.null(x)){
+    stop("Please provide the name of the input object!", call.=FALSE)
+  }
+
+  # the input variable might be given as column table (i.e. D$x)
+  # or just as a vector not attached to a table (i.e. x)
+  # we have to make sure the function deals with each case
+  xnames <- extract(x)
+  varname <- xnames$elements
+  obj2lookfor <- xnames$holders
+
+  # check if the input object(s) is(are) defined in all the studies
+  if(is.na(obj2lookfor)){
+    defined <- isDefined(datasources, varname)
+  }else{
+    defined <- isDefined(datasources, obj2lookfor)
+  }
+
+  # call the internal function that checks the input object is of the same class in all studies.
+  typ <- checkClass(datasources, x)
+
+  # call the internal function that checks the input object(s) is(are) of the same class in all studies.
+  if(!('numeric' %in% typ) && !('integer' %in% typ)){
+      stop("Only objects of type 'numeric' or 'integer' are allowed.", call.=FALSE)
+  }
+
+  # create a name by default if the user did not provide a name for the new variable
+  if(is.null(newobj)){
+    newobj <- "sqrt.newobj"
+  }
+
+  # call the server side function that does the operation
+  cally <- call("sqrtDS", x)
+  DSI::datashield.assign(datasources, newobj, cally)
+
+  # check that the new object has been created and display a message accordingly
+  finalcheck <- isAssigned(datasources, newobj)
+
+}