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ds.reShape.R
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ds.reShape.R
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#' @title Reshape server-side grouped data
#' @description Reshapes a data frame containing longitudinal or
#' otherwise grouped data from 'wide' to 'long' format or vice-versa.
#' @details This function is based on the native R function \code{reshape}.
#' It reshapes a data frame containing longitudinal or otherwise grouped data
#' between 'wide' format with repeated
#' measurements in separate columns of the same record and 'long' format with the repeated
#' measurements in separate records. The reshaping can be in either direction.
#' Server function called: \code{reShapeDS}
#' @param data.name a character string specifying the name of the data frame to be reshaped.
#' @param varying names of sets of variables in the wide format that correspond to single
#' variables in 'long' format.
#' @param v.names the names of variables in the 'long' format that correspond to multiple variables
#' in the 'wide' format.
#' @param timevar.name the variable in 'long' format that differentiates multiple
#' records from the same group or individual.
#' If more than one record matches, the first will be taken.
#' @param idvar.name names of one or more variables in 'long' format that identify multiple
#' records from the same group/individual. These variables may also be present in 'wide' format.
#' @param drop a vector of names of variables to drop before reshaping. This can simplify the
#' resultant output.
#' @param direction a character string that partially matched to either 'wide' to reshape from
#' 'long' to 'wide' format, or 'long' to reshape from 'wide' to 'long' format.
#' @param sep a character vector of length 1, indicating a separating character in the variable
#' names in the 'wide' format. This is used for creating good \code{v.names} and times arguments based
#' on the names in the \code{varying} argument. This is also used to create variable names
#' when reshaping
#' to 'wide' format.
#' @param newobj a character string that provides the name for the output object
#' that is stored on the data servers.
#' Default \code{reshape.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.reShape} returns to the server-side a reshaped data frame
#' converted from 'long' to 'wide' format or from 'wide' to long' format.
#' Also, two validity messages are returned to the client-side
#' indicating whether the new object has been created in each data source and if so whether
#' it is in a valid form.
#' @author DataSHIELD Development Team
#' @examples
#' \dontrun{
#'
#' ## Version 6, for version 5 see Wiki
#' # Connecting to the Opal servers
#'
#' require('DSI')
#' require('DSOpal')
#' require('dsBaseClient')
#'
#' builder <- DSI::newDSLoginBuilder()
#' builder$append(server = "study1",
#' url = "http://192.168.56.100:8080/",
#' user = "administrator", password = "datashield_test&",
#' table = "SURVIVAL.EXPAND_NO_MISSING1", driver = "OpalDriver")
#' builder$append(server = "study2",
#' url = "http://192.168.56.100:8080/",
#' user = "administrator", password = "datashield_test&",
#' table = "SURVIVAL.EXPAND_NO_MISSING2", driver = "OpalDriver")
#' builder$append(server = "study3",
#' url = "http://192.168.56.100:8080/",
#' user = "administrator", password = "datashield_test&",
#' table = "SURVIVAL.EXPAND_NO_MISSING3", driver = "OpalDriver")
#' logindata <- builder$build()
#'
#' # Log onto the remote Opal training servers
#' connections <- DSI::datashield.login(logins = logindata, assign = TRUE, symbol = "D")
#'
#' #Reshape server-side grouped data
#'
#' ds.reShape(data.name = "D",
#' v.names = "age.60",
#' timevar.name = "time.id",
#' idvar.name = "id",
#' direction = "wide",
#' newobj = "reshape1_obj",
#' datasources = connections)
#'
#' # Clear the Datashield R sessions and logout
#' datashield.logout(connections)
#'}
#'
#' @export
ds.reShape <- function(data.name=NULL, varying=NULL, v.names=NULL, timevar.name="time", idvar.name="id",
drop=NULL, direction=NULL, sep=".", newobj="newObject", datasources=NULL){
# look for DS connections
if(is.null(datasources)){
datasources <- datashield.connections_find()
}
if(is.null(data.name)){
stop("Please provide the name of the list that holds the input vectors!", call.=FALSE)
}
if (!is.character(sep) || (nchar(sep) != 1)){
stop("'sep' must be a character string", call.=FALSE)
}
if(!is.null(varying)){
varying.transmit <- paste(varying,collapse=",")
}else{
varying.transmit <- NULL
}
if(!is.null(v.names)){
v.names.transmit <- paste(v.names,collapse=",")
}else{
v.names.transmit <- NULL
}
if(!is.null(drop)){
drop.transmit <- paste(drop,collapse=",")
}else{
drop.transmit <- NULL
}
##############################
# call the server side function
calltext <- call("reShapeDS", data.name, varying.transmit, v.names.transmit, timevar.name, idvar.name, drop.transmit, direction, sep)
DSI::datashield.assign(datasources, newobj, calltext)
#############################################################################################################
#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.reShape