// [[Rcpp::export(".cyclopsFinalizeData")]]
void cyclopsFinalizeData(
Environment x,
bool addIntercept,
SEXP sexpOffsetCovariate,
bool offsetAlreadyOnLogScale,
bool sortCovariates,
SEXP sexpCovariatesDense,
bool magicFlag = false) {
using namespace bsccs;
XPtr<ModelData> data = parseEnvironmentForPtr(x);
if (data->getIsFinalized()) {
::Rf_error("OHDSI data object is already finalized");
}
if (addIntercept) {
if (data->getHasInterceptCovariate()) {
::Rf_error("OHDSI data object already has an intercept");
}
// TODO add intercept as INTERCEPT_TYPE if magicFlag == true
data->insert(0, DENSE); // add to front, TODO fix if offset
data->setHasInterceptCovariate(true);
// CompressedDataColumn& intercept = data->getColumn(0);
const size_t numRows = data->getNumberOfRows();
for (size_t i = 0; i < numRows; ++i) {
data->getColumn(0).add_data(i, static_cast<real>(1.0));
}
}
if (!Rf_isNull(sexpOffsetCovariate)) {
// TODO handle offset
IdType covariate = as<IdType>(sexpOffsetCovariate);
int index;
if (covariate == -1) { // TODO Bad, magic number
//std::cout << "Trying to convert time to offset" << std::endl;
//data->push_back(NULL, NULL, offs.begin(), offs.end(), DENSE); // TODO Do not make copy
//data->push_back(NULL, &(data->getTimeVectorRef()), DENSE);
data->moveTimeToCovariate(true);
index = data->getNumberOfColumns() - 1;
} else {
index = data->getColumnIndexByName(covariate);
if (index == -1) {
std::ostringstream stream;
stream << "Variable " << covariate << " not found.";
stop(stream.str().c_str());
//error->throwError(stream);
}
}
data->moveToFront(index);
data->getColumn(0).add_label(-1); // TODO Generic label for offset?
data->setHasOffsetCovariate(true);
}
if (data->getHasOffsetCovariate() && !offsetAlreadyOnLogScale) {
//stop("Transforming the offset is not yet implemented");
data->getColumn(0).transform([](real x) {
return std::log(x);
});
}
if (!Rf_isNull(sexpCovariatesDense)) {
// TODO handle dense conversion
ProfileVector covariates = as<ProfileVector>(sexpCovariatesDense);
for (auto it = covariates.begin(); it != covariates.end(); ++it) {
IdType index = data->getColumnIndex(*it);
data->getColumn(index).convertColumnToDense(data->getNumberOfRows());
}
}
data->setIsFinalized(true);
}
