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ds.dataFrameSubset.R
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ds.dataFrameSubset.R
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#' @title Subsetting data frames in the server-side
#' @description Subsets a data frame by rows and/or by columns.
#' @details Subset a pre-existing data frame using the standard
#' set of Boolean operators (\code{==, !=, >, >=, <, <=}).
#' The subsetting is made by rows, but it is also possible to select
#' columns to keep or remove. Instead, if you
#' wish to keep all rows in the subset (e.g. if the primary plan is to subset by columns
#' and not by rows) the \code{V1.name} and \code{V2.name} parameters can be used
#' to specify a vector of the same length
#' as the data frame to be subsetted in each study in which every element is 1 and
#' there are no missing values. For more information see the example 2 below.
#'
#' Server functions called: \code{dataFrameSubsetDS1} and \code{dataFrameSubsetDS2}
#'
#' @param df.name a character string providing the name of the data frame to be subseted.
#' @param V1.name A character string specifying the name of the vector
#' to which the Boolean operator is to be applied to define the subset.
#' For more information see details.
#' @param V2.name A character string specifying the name of the vector to compare
#' with \code{V1.name}.
#' @param Boolean.operator A character string specifying one of six possible Boolean operators:
#' \code{'==', '!=', '>', '>=', '<'} and \code{'<='}.
#' @param keep.cols a numeric vector specifying the numbers of the columns to be kept in the
#' final subset.
#' @param rm.cols a numeric vector specifying the numbers of the columns to be removed from
#' the final subset.
#' @param keep.NAs logical, if TRUE the missing values are included in the subset.
#' If FALSE or NULL all rows with at least one missing values are removed from the subset.
#' @param newobj a character string that provides the name for the output
#' object that is stored on the data servers. Default \code{dataframesubset.newobj}.
#' @param datasources a list of \code{\link{DSConnection-class}} objects obtained after login.
#' If the \code{datasources}
#' the default set of connections will be used: see \code{\link{datashield.connections_default}}.
#' @param notify.of.progress specifies if console output should be produced to indicate
#' progress. Default FALSE.
#' @return \code{ds.dataFrameSubset} returns
#' the object specified by the \code{newobj} argument
#' which is written to the server-side.
#' Also, two validity messages are returned to the client-side indicating
#' the name of the \code{newobj} which has been created in each data source
#' and if it is in a valid form.
#' @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$append(server = "study1",
#' url = "http://192.168.56.100:8080/",
#' user = "administrator", password = "datashield_test&",
#' table = "CNSIM.CNSIM1", driver = "OpalDriver")
#' builder$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()
#'
#' connections <- DSI::datashield.login(logins = logindata, assign = TRUE, symbol = "D")
#'
#' # Subsetting a data frame
#' #Example 1: Include some rows and all columns in the subset
#' ds.dataFrameSubset(df.name = "D",
#' V1.name = "D$LAB_TSC",
#' V2.name = "D$LAB_TRIG",
#' Boolean.operator = ">",
#' keep.cols = NULL, #All columns are included in the new subset
#' rm.cols = NULL, #All columns are included in the new subset
#' keep.NAs = FALSE, #All rows with NAs are removed
#' newobj = "new.subset",
#' datasources = connections[1],#only the first server is used ("study1")
#' notify.of.progress = FALSE)
#' #Example 2: Include all rows and some columns in the new subset
#' #Select complete cases (rows without NA)
#' ds.completeCases(x1 = "D",
#' newobj = "complet",
#' datasources = connections)
#' #Create a vector with all ones
#' ds.make(toAssign = "complet$LAB_TSC-complet$LAB_TSC+1",
#' newobj = "ONES",
#' datasources = connections)
#' #Subset the data
#' ds.dataFrameSubset(df.name = "complet",
#' V1.name = "ONES",
#' V2.name = "ONES",
#' Boolean.operator = "==",
#' keep.cols = c(1:4,10), #only columns 1, 2, 3, 4 and 10 are selected
#' rm.cols = NULL,
#' keep.NAs = FALSE,
#' newobj = "subset.all.rows",
#' datasources = connections, #all servers are used
#' notify.of.progress = FALSE)
#'
#' # Clear the Datashield R sessions and logout
#' datashield.logout(connections)
#'
#' }
#' @author DataSHIELD Development Team
#' @export
ds.dataFrameSubset<-function(df.name=NULL, V1.name=NULL, V2.name=NULL, Boolean.operator=NULL, keep.cols=NULL, rm.cols=NULL, keep.NAs=NULL, newobj=NULL, datasources=NULL, notify.of.progress=FALSE){
# look for DS connections
if(is.null(datasources)){
datasources <- datashield.connections_find()
}
# check if user has provided the name of the data.frame to be subsetted
if(is.null(df.name)){
stop("Please provide the name of the data.frame to be subsetted as a character string: eg 'xxx'", call.=FALSE)
}
# check if user has provided the name of the column or scalar that holds V1
if(is.null(V1.name)){
stop("Please provide the name of the column or scalar that holds V1 as a character string: eg 'xxx' or '3'", call.=FALSE)
}
# check if user has provided the name of the column or scalar that holds V2
if(is.null(V2.name)){
stop("Please provide the name of the column or scalar that holds V2 as a character string: eg 'xxx' or '3'", call.=FALSE)
}
# check if user has provided a Boolean operator in character format: eg '==' or '>=' or '<' or '!='
if(is.null(Boolean.operator)){
stop("Please provide a Boolean operator in character format: eg '==' or '>=' or '<' or '!='", call.=FALSE)
}
#if keep.NAs is set as NULL convert to FALSE as otherwise the call to datashield.assign will fail
if(is.null(keep.NAs)){
keep.NAs<-FALSE
}
#convert Boolean operator to numeric
BO.n<-0
if(Boolean.operator == "=="){
BO.n<-1
}
if(Boolean.operator == "!="){
BO.n<-2
}
if(Boolean.operator == "<"){
BO.n<-3
}
if(Boolean.operator == "<="){
BO.n<-4
}
if(Boolean.operator == ">"){
BO.n<-5
}
if(Boolean.operator == ">="){
BO.n<-6
}
# if no value spcified for output object, then specify a default
if(is.null(newobj)){
newobj <- "dataframesubset.newobj"
}
if(!is.null(keep.cols)){
keep.cols<-paste0(as.character(keep.cols),collapse=",")
}
if(!is.null(rm.cols)){
rm.cols<-paste0(as.character(rm.cols),collapse=",")
}
calltext1 <- call("dataFrameSubsetDS1", df.name, V1.name, V2.name, BO.n, keep.cols, rm.cols, keep.NAs)
return.warning.message<-DSI::datashield.aggregate(datasources, calltext1)
calltext2 <- call("dataFrameSubsetDS2", df.name, V1.name, V2.name, BO.n, keep.cols, rm.cols, keep.NAs)
DSI::datashield.assign(datasources, newobj, calltext2)
numsources<-length(datasources)
for(s in 1:numsources){
num.messages<-length(return.warning.message[[s]])
if (notify.of.progress)
{
if(num.messages==1){
cat("\nSource",s,"\n",return.warning.message[[s]][[1]],"\n")
}else{
cat("\nSource",s,"\n")
for(m in 1:(num.messages-1)){
cat(return.warning.message[[s]][[m]],"\n")
}
cat(return.warning.message[[s]][[num.messages]],"\n")
}
}
}
#############################################################################################################
#DataSHIELD CLIENTSIDE MODULE: CHECK KEY DATA OBJECTS SUCCESSFULLY CREATED #
#
#SET APPROPRIATE PARAMETERS FOR THIS PARTICULAR FUNCTION #
test.obj.name<-newobj #
# #
#
# CALL SEVERSIDE FUNCTION #
calltext <- call("testObjExistsDS", test.obj.name) #
#
object.info<-DSI::datashield.aggregate(datasources, calltext) #
#
# CHECK IN EACH SOURCE WHETHER OBJECT NAME EXISTS #
# AND WHETHER OBJECT PHYSICALLY EXISTS WITH A NON-NULL CLASS #
num.datasources<-length(object.info) #
#
#
obj.name.exists.in.all.sources<-TRUE #
obj.non.null.in.all.sources<-TRUE #
#
for(j in 1:num.datasources){ #
if(!object.info[[j]]$test.obj.exists){ #
obj.name.exists.in.all.sources<-FALSE #
} #
if(is.null(object.info[[j]]$test.obj.class) || object.info[[j]]$test.obj.class=="ABSENT"){ #
obj.non.null.in.all.sources<-FALSE #
} #
} #
#
if(obj.name.exists.in.all.sources && obj.non.null.in.all.sources){ #
#
return.message<- #
paste0("A data object <", test.obj.name, "> has been created in all specified data sources") #
#
#
}else{ #
#
return.message.1<- #
paste0("Error: A valid data object <", test.obj.name, "> does NOT exist in ALL specified data sources") #
#
return.message.2<- #
paste0("It is either ABSENT and/or has no valid content/class,see return.info above") #
#
return.message.3<- #
paste0("Please use ds.ls() to identify where missing") #
#
#
return.message<-list(return.message.1,return.message.2,return.message.3) #
#
} #
#
calltext <- call("messageDS", test.obj.name) #
studyside.message<-DSI::datashield.aggregate(datasources, calltext) #
#
no.errors<-TRUE #
for(nd in 1:num.datasources){ #
if(studyside.message[[nd]]!="ALL OK: there are no studysideMessage(s) on this datasource"){ #
no.errors<-FALSE #
} #
} #
#
#
if(no.errors){ #
validity.check<-paste0("<",test.obj.name, "> appears valid in all sources") #
return(list(is.object.created=return.message,validity.check=validity.check)) #
} #
#
if(!no.errors){ #
validity.check<-paste0("<",test.obj.name,"> invalid in at least one source. See studyside.messages:") #
return(list(is.object.created=return.message,validity.check=validity.check, #
studyside.messages=studyside.message)) #
} #
#
#END OF CHECK OBJECT CREATED CORECTLY MODULE #
#############################################################################################################
}
#ds.dataFrameSubset