// Based on table()
// dataframe {
// for each column get the num of dims.tfm
// get size of the resulting talbe
// finally tabulate by the bins meaning how many are there
// each value will correspond to its index in the dim array.
// this is just indexing by a set of values, then you go to there and find it.
// }
// [[Rcpp::export]]
Rcpp::IntegerVector table_cpp(const RObject & input, const RObject & columns) {
if(!is<DataFrame>(input)) stop("Must be a data frame.");
DataFrame data = as<DataFrame>(input);
if(!is<CharacterVector>(columns)) stop("Must be character vector.");
CharacterVector cols = as<CharacterVector>(columns);
data = data[cols];
const R_xlen_t ncols = data.ncol();
if (ncols == 0) stop("No columns in data frame.");
const IntegerVector & column = data.at(0);
// There is a single entry for each row
IntegerVector to_tabulate = no_init(column.size());
to_tabulate.fill(1);
// The product of dimensions.
R_xlen_t pd = 1;
IntegerVector dims(ncols);
List dimnames(ncols);
dimnames.names() = data.names();
for (R_xlen_t i = 0; i < ncols; i++) {
const IntegerVector & a = data.at(i);
if(!Rf_isFactor(a)) stop("Not a factor.");
const CharacterVector & factorLevels = a.attr("levels");
R_xlen_t nl = factorLevels.size();
to_tabulate = to_tabulate + pd * (a - 1L);
pd = pd * nl ;
dims.at(i) = nl;
dimnames.at(i) = factorLevels;
}
to_tabulate = na_omit(to_tabulate);
IntegerVector tbl = tabulate_cpp(to_tabulate, pd);
tbl.attr("dim") = dims;
tbl.attr("dimnames") = dimnames;
tbl.attr("class") = "table";
return tbl;
}
