[Rcpp-devel] Using data-frames as sets of rows (e.g. using R data-frames as lookup tables in C++)

[Mark Clements]

By my understanding, Rcpp is better suited to working with data-frames as columns rather than working with data-frames as a set of rows. However, occasionally it may be useful to work with the set of rows. How have others considered this use case?

[As a motivating example based on simulations in C++, we want to pass data-frames from R for use as look-up tables in C++ (cf. passing transformed data back to R). The STL container std::map is well suited to this task, particularly as it provides ordered keys.

In the following code, we define a template class Table1D which reads in a data-frame and defines the map key with the first column and the map value with the second column. The only sophistication here is (i) using std::greater as a comparison function and (ii) using Rcpp traits. Note that calling the function from R is only shown for demonstration.

require(inline)
lookup <- rcpp(signature(df="data.frame",x="numeric"),
            body="
  Table1D<double,double> table = Table1D<double,double>(df);
  return wrap(table(as<double>(x)));
",
            includes="
#include <map>
#include <functional>
template <class Index, class Outcome>
class Table1D {
public:
  std::map<Index,Outcome,std::greater<Index> > data;
  Table1D(DataFrame df, int iIndex = 0, int iOutcome = 1) {
    Vector<Rcpp::traits::r_sexptype_traits<Index>::rtype> df0 = df[iIndex];
    Vector<Rcpp::traits::r_sexptype_traits<Outcome>::rtype> df1 = df[iOutcome];
    for (size_t i=0; i<df0.size(); i++) {
      data[df0[i]] = df1[i];
    }
  }
  virtual Outcome lookup(Index index) {
    return data.lower_bound(index)->second;
  }
  virtual Outcome operator()(Index index) {
    return lookup(index);
  }
};
")
lookup(data.frame(as.numeric(1:1000000),10.0*as.numeric(1:1000000)), 12345.5)

See also https://github.com/mclements/microsimulation/blob/master/src/rcpp_table.h for an extension to higher dimensions.]

Sincerely, Mark.
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