59 lines
No EOL
2.2 KiB
R
59 lines
No EOL
2.2 KiB
R
|
|
# Internal function that takes a formula and processes it for use in the Java
|
|
# code. existingCovariateList is optional; if not provided then a new one is
|
|
# created internally.
|
|
processFormula <- function(formula, data, covariateList.java = NULL){
|
|
|
|
# Having an R copy of the data loaded at the same time can be wasteful; we
|
|
# also allow users to provide an environment of the data which gets removed
|
|
# after being imported into Java
|
|
if(class(data) == "environment"){
|
|
if(is.null(data$data)){
|
|
stop("When providing an environment with the dataset, the environment must contain an item called 'data'")
|
|
}
|
|
|
|
env <- data
|
|
data <- env$data
|
|
env$data <- NULL
|
|
gc()
|
|
}
|
|
|
|
yVar <- formula[[2]]
|
|
|
|
responses <- NULL
|
|
variablesToDrop <- character(0)
|
|
|
|
# yVar is a call object; as.character(yVar) will be the different components, including the parameters.
|
|
# if the length of yVar is > 1 then it's a function call. If the length is 1, and it's not in data,
|
|
# then we also need to explicitly evaluate it
|
|
if(class(yVar) == "call" || !(as.character(yVar) %in% colnames(data))){
|
|
# yVar is a function like CR_Response
|
|
responses <- eval(expr=yVar, envir=data)
|
|
|
|
if(class(formula[[3]]) == "name" && as.character(formula[[3]])=="."){
|
|
# do any of the variables match data in data? We need to track that so we can drop them later
|
|
variablesToDrop <- as.character(yVar)[as.character(yVar) %in% names(data)]
|
|
}
|
|
|
|
formula[[2]] <- NULL
|
|
|
|
} else if(class(yVar) == "name"){ # and implicitly yVar is contained in data
|
|
variablesToDrop <- as.character(yVar)
|
|
}
|
|
|
|
# Includes responses which we may need to later cut out if `.` was used on the
|
|
# right-hand-side
|
|
filteredData <- stats::model.frame(formula=formula, data=data, na.action=stats::na.pass)
|
|
|
|
if(is.null(responses)){ # If this if-statement runs then we have a simple (i.e. numeric) response
|
|
responses <- stats::model.response(filteredData)
|
|
}
|
|
|
|
# remove any response variables on the right-hand-side
|
|
covariateData <- filteredData[, !(names(filteredData) %in% variablesToDrop), drop=FALSE]
|
|
|
|
|
|
dataset <- loadData(covariateData, colnames(covariateData), responses, covariateList.java = covariateList.java)
|
|
|
|
return(dataset)
|
|
} |