R/ds.recodeValues.R
In datashield/dsBaseClient: DataSHIELD Client Functions
Defines functions
ds.recodeValues
Documented in
ds.recodeValues
#' @title Recodes server-side variable values
#' @description This function takes specified values of elements in a vector and converts
#' them to a matched set of alternative specified values.
#' @details This function recodes individual values with new individual values. This can
#' apply to numeric and character values, factor levels and NAs. One particular use of
#' \code{ds.recodeValues} is to convert NAs to an explicit value. This value is specified
#' in the argument \code{missing}. If tthe user want to recode only missing values, then it
#' should also specify an identical vector of values in both arguments \code{values2replace.vector}
#' and \code{new.values.vector} (see Example 2 below).
#' Server function called: \code{recodeValuesDS}
#' @param var.name a character string providing the name of the variable to be recoded.
#' @param values2replace.vector a numeric or character vector specifying the values
#' in the variable \code{var.name} to be replaced.
#' @param new.values.vector a numeric or character vector specifying the new values.
#' @param missing If supplied, any missing values in var.name will be replaced by this value.
#' Must be of length 1. If the analyst want to recode only missing values then it should also
#' specify an identical vector of values in both arguments \code{values2replace.vector} and
#' \code{new.values.vector}. Otherwise please look the \code{ds.replaceNA} function.
#' @param newobj a character string that provides the name for the output object
#' that is stored on the data servers.
#' Default \code{recodevalues.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}}.
#' @param notify.of.progress logical. If TRUE console output should be produced to indicate
#' progress. Default FALSE.
#' @return Assigns to each server a new variable with the recoded values.
#' 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 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")
#'
#' # Example 1: recode the levels of D$GENDER
#' ds.recodeValues(var.name = "D$GENDER",
#' values2replace.vector = c(0,1),
#' new.values.vector = c(10,20),
#' newobj = 'gender_recoded',
#' datasources = connections)
#'
#' # Example 2: recode NAs in D$PM_BMI_CATEGORICAL
#' ds.recodeValues(var.name = "D$PM_BMI_CATEGORICAL",
#' values2replace.vector = c(1,2),
#' new.values.vector = c(1,2),
#' missing = 99,
#' newobj = 'bmi_recoded'
#' datasources = connections)
#'
#' # Clear the Datashield R sessions and logout
#' datashield.logout(connections)
#'
#' }
#' @export
#'
ds.recodeValues <- function(var.name=NULL, values2replace.vector=NULL, new.values.vector=NULL,
missing=NULL, newobj=NULL, datasources=NULL, notify.of.progress=FALSE){
# look for DS connections
if(is.null(datasources)){
datasources <- datashield.connections_find()
}
# ensure datasources is a list of DSConnection-class
if(!(is.list(datasources) && all(unlist(lapply(datasources, function(d) {methods::is(d,"DSConnection")}))))){
stop("The 'datasources' were expected to be a list of DSConnection-class objects", call.=FALSE)
}
# check user has provided the name of the variable to be recoded
if(is.null(var.name)){
stop("Please provide the name of the variable to be recoded: eg 'xxx'", call.=FALSE)
}
# check if the input object is defined in all the studies
isDefined(datasources, var.name)
# check user has provided the vector specifying the set of values to be replaced
if(is.null(values2replace.vector)){
stop("Please provide a vector in the 'values2replace.vector' argument specifying
the values to be replaced eg c(1,7)", call.=FALSE)
}
# check user has provided the vector specifying the set of values to replace them with
if(is.null(values2replace.vector)){
stop("Please provide a vector specifying the new values to be set eg c(3,4)", call.=FALSE)
}
# check values2replace.vector and new.values.vector have the same length
if(length(values2replace.vector) != length(new.values.vector)){
stop("Please ensure that values2replace.vector and new.values.vector have same length and are in the same order", call.=FALSE)
}
# check no duplicate values in values2replace.vector
if(length(values2replace.vector) != length(unique(values2replace.vector))){
stop("No value may appear more than once in the values2replace.vector", call.=FALSE)
}
# simple work around for a bug in the format for values2replace.vector
if(any(is.na(values2replace.vector))){
stop("To recode NAs you need to use the 'missing' argument", call.=FALSE)
}
if(!is.null(values2replace.vector) & !is.null(new.values.vector)){
values2replace.transmit <- paste0(as.character(values2replace.vector), collapse=",")
new.values.transmit <- paste0(as.character(new.values.vector), collapse=",")
}else{
values2replace.transmit <- NULL
new.values.transmit <- NULL
}
if(is.null(newobj)){
newobj <- paste0(var.name, "_recoded")
}
calltext <- call("recodeValuesDS", var.name, values2replace.transmit, new.values.transmit, missing)
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) || ("ABSENT" %in% object.info[[j]]$test.obj.class)){ #
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.recodeValues
datashield/dsBaseClient documentation built on May 16, 2023, 10:19 p.m.
R Package Documentation
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Defines functions ds.recodeValues
Documented in ds.recodeValues
#' @title Recodes server-side variable values
#' @description This function takes specified values of elements in a vector and converts
#' them to a matched set of alternative specified values.
#' @details This function recodes individual values with new individual values. This can
#' apply to numeric and character values, factor levels and NAs. One particular use of
#' \code{ds.recodeValues} is to convert NAs to an explicit value. This value is specified
#' in the argument \code{missing}. If tthe user want to recode only missing values, then it
#' should also specify an identical vector of values in both arguments \code{values2replace.vector}
#' and \code{new.values.vector} (see Example 2 below).
#' Server function called: \code{recodeValuesDS}
#' @param var.name a character string providing the name of the variable to be recoded.
#' @param values2replace.vector a numeric or character vector specifying the values
#' in the variable \code{var.name} to be replaced.
#' @param new.values.vector a numeric or character vector specifying the new values.
#' @param missing If supplied, any missing values in var.name will be replaced by this value.
#' Must be of length 1. If the analyst want to recode only missing values then it should also
#' specify an identical vector of values in both arguments \code{values2replace.vector} and
#' \code{new.values.vector}. Otherwise please look the \code{ds.replaceNA} function.
#' @param newobj a character string that provides the name for the output object
#' that is stored on the data servers.
#' Default \code{recodevalues.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}}.
#' @param notify.of.progress logical. If TRUE console output should be produced to indicate
#' progress. Default FALSE.
#' @return Assigns to each server a new variable with the recoded values.
#' 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 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$build()
#'
#' connections <- DSI::datashield.login(logins = logindata, assign = TRUE, symbol = "D")
#'
#' # Example 1: recode the levels of D$GENDER
#' ds.recodeValues(var.name = "D$GENDER",
#' values2replace.vector = c(0,1),
#' new.values.vector = c(10,20),
#' newobj = 'gender_recoded',
#' datasources = connections)
#'
#' # Example 2: recode NAs in D$PM_BMI_CATEGORICAL
#' ds.recodeValues(var.name = "D$PM_BMI_CATEGORICAL",
#' values2replace.vector = c(1,2),
#' new.values.vector = c(1,2),
#' missing = 99,
#' newobj = 'bmi_recoded'
#' datasources = connections)
#'
#' # Clear the Datashield R sessions and logout
#' datashield.logout(connections)
#'
#' }
#' @export
#'
ds.recodeValues <- function(var.name=NULL, values2replace.vector=NULL, new.values.vector=NULL,
missing=NULL, newobj=NULL, datasources=NULL, notify.of.progress=FALSE){
# look for DS connections
if(is.null(datasources)){
datasources <- datashield.connections_find()
}
# ensure datasources is a list of DSConnection-class
if(!(is.list(datasources) && all(unlist(lapply(datasources, function(d) {methods::is(d,"DSConnection")}))))){
stop("The 'datasources' were expected to be a list of DSConnection-class objects", call.=FALSE)
}
# check user has provided the name of the variable to be recoded
if(is.null(var.name)){
stop("Please provide the name of the variable to be recoded: eg 'xxx'", call.=FALSE)
}
# check if the input object is defined in all the studies
isDefined(datasources, var.name)
# check user has provided the vector specifying the set of values to be replaced
if(is.null(values2replace.vector)){
stop("Please provide a vector in the 'values2replace.vector' argument specifying
the values to be replaced eg c(1,7)", call.=FALSE)
}
# check user has provided the vector specifying the set of values to replace them with
if(is.null(values2replace.vector)){
stop("Please provide a vector specifying the new values to be set eg c(3,4)", call.=FALSE)
}
# check values2replace.vector and new.values.vector have the same length
if(length(values2replace.vector) != length(new.values.vector)){
stop("Please ensure that values2replace.vector and new.values.vector have same length and are in the same order", call.=FALSE)
}
# check no duplicate values in values2replace.vector
if(length(values2replace.vector) != length(unique(values2replace.vector))){
stop("No value may appear more than once in the values2replace.vector", call.=FALSE)
}
# simple work around for a bug in the format for values2replace.vector
if(any(is.na(values2replace.vector))){
stop("To recode NAs you need to use the 'missing' argument", call.=FALSE)
}
if(!is.null(values2replace.vector) & !is.null(new.values.vector)){
values2replace.transmit <- paste0(as.character(values2replace.vector), collapse=",")
new.values.transmit <- paste0(as.character(new.values.vector), collapse=",")
}else{
values2replace.transmit <- NULL
new.values.transmit <- NULL
}
if(is.null(newobj)){
newobj <- paste0(var.name, "_recoded")
}
calltext <- call("recodeValuesDS", var.name, values2replace.transmit, new.values.transmit, missing)
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]]$test.obj.class) || ("ABSENT" %in% object.info[[j]]$test.obj.class)){ #
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.recodeValues
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