#' @title Calls nlme::groupedData on the provided arguments
#' @description See the documentation of groupedData in package nlme
#' @param newobj a character, name of the new dataframe
#' @param ... further arguments to be passed to nlme:groupedData. The data argument must pe passed as a character, the name of the input dataframe
#' @param async same as in datashield.assign
#' @param wait same as in datashield.assign
#' @param datasources same as in datashield.assign
dssNlme_groupedData <- function(newobj, ..., async = TRUE, wait = TRUE, datasources = NULL){
if(is.null(datasources)){
datasources <- dsBaseClient_findLoginObjects()
}
arglist <- list(...) # pass the args list almost as is to the local nodes
if(typeof(arglist$formula) == 'language'){
arglist$formula <- Reduce(paste, deparse(arglist$formula)) # Reduce for formulas longer than 60 chars - deparse splits them into a vector
}
arglist <- .encode.arg(arglist)
cally <- paste0('groupedDataDSS("', arglist, '")')
opal::datashield.assign(datasources, symbol = newobj, value = as.symbol(cally), async = async, wait = wait)
}
#' @title Calls nlme::lme on the provided arguments
#' @description See the documentation of lme in package nlme
#' @param newobj a character, name of the new dataframe
#' @param ... further arguments to be passed to nlme::lme. The data argument must pe passed as a character, the name of the input dataframe
#' @param async same as in datashield.assign
#' @param wait same as in datashield.assign
#' @param datasources same as in datashield.assign
#' @return a stripped down lmeObject (without the 'data' and 'call' elements). See the documentation for lme and lmeObject in package lme.
#' @examples
#' # open a local pseudo connection:
#' opals <- dssCreatePseudoServers(servers = 1, tie_first_to_GlobalEnv = TRUE)
#' # load the Orthodont dataset
#' datashield.aggregate(opals[1], as.symbol('partialData("Orthodont", NULL, NULL, "nlme")'))
#' dssNlme_groupedData(newobj = 'grouped', formula = distance ~ age | Subject, data ='Orthodont', async = FALSE, datasources = opals[1] )
#' lme.model <- dssNlme_lme(fixed = distance ~ age, data = 'grouped', random = ~ 1, async = FALSE, datasources = opals[1])
#' summary(lme.model[[1]])
#'
dssNlme_lme <- function(..., async = TRUE, wait = TRUE, datasources = NULL){
if(is.null(datasources)){
datasources <- dsBaseClient_findLoginObjects()
}
arglist <- list(...) # pass the args list almost as is to the local nodes
arglist <- sapply(arglist, function(x){
if(typeof(x)=='language'){
#return(Reduce(paste0, deparse(arglist[x]))) # Reduce for formulas longer than 60 chars - deparse splits them into a vector
return(deparse(x))
} else {
return(x)
}
}, simplify = FALSE)
arglist <- sapply(arglist, function(x) paste(x, collapse = ''), simplify = FALSE)
arglist <- .encode.arg(arglist)
cally <- paste0('nlme_lmeDSS("', arglist, '")')
opal::datashield.aggregate(datasources, as.symbol(cally), async = async, wait = wait)
}
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