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<p class="MsoNormal">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? <o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">[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.<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">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.<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">require(inline)<o:p></o:p></p>
<p class="MsoNormal">lookup <- rcpp(signature(df="data.frame",x="numeric"),<o:p></o:p></p>
<p class="MsoNormal"> body="<o:p></o:p></p>
<p class="MsoNormal"> Table1D<double,double> table = Table1D<double,double>(df);<o:p></o:p></p>
<p class="MsoNormal"> return wrap(table(as<double>(x)));<o:p></o:p></p>
<p class="MsoNormal">",<o:p></o:p></p>
<p class="MsoNormal"> includes="<o:p></o:p></p>
<p class="MsoNormal">#include <map><o:p></o:p></p>
<p class="MsoNormal">#include <functional><o:p></o:p></p>
<p class="MsoNormal">template <class Index, class Outcome><o:p></o:p></p>
<p class="MsoNormal">class Table1D {<o:p></o:p></p>
<p class="MsoNormal">public:<o:p></o:p></p>
<p class="MsoNormal"> std::map<Index,Outcome,std::greater<Index> > data;<o:p></o:p></p>
<p class="MsoNormal"> Table1D(DataFrame df, int iIndex = 0, int iOutcome = 1) { <o:p>
</o:p></p>
<p class="MsoNormal"> Vector<Rcpp::traits::r_sexptype_traits<Index>::rtype> df0 = df[iIndex];<o:p></o:p></p>
<p class="MsoNormal"> Vector<Rcpp::traits::r_sexptype_traits<Outcome>::rtype> df1 = df[iOutcome];<o:p></o:p></p>
<p class="MsoNormal"> for (size_t i=0; i<df0.size(); i++) {<o:p></o:p></p>
<p class="MsoNormal"> data[df0[i]] = df1[i];<o:p></o:p></p>
<p class="MsoNormal"> }<o:p></o:p></p>
<p class="MsoNormal"> }<o:p></o:p></p>
<p class="MsoNormal"> virtual Outcome lookup(Index index) {<o:p></o:p></p>
<p class="MsoNormal"> return data.lower_bound(index)->second;<o:p></o:p></p>
<p class="MsoNormal"> }<o:p></o:p></p>
<p class="MsoNormal"> virtual Outcome operator()(Index index) {<o:p></o:p></p>
<p class="MsoNormal"> return lookup(index);<o:p></o:p></p>
<p class="MsoNormal"> }<o:p></o:p></p>
<p class="MsoNormal">};<o:p></o:p></p>
<p class="MsoNormal">")<o:p></o:p></p>
<p class="MsoNormal">lookup(data.frame(as.numeric(1:1000000),10.0*as.numeric(1:1000000)), 12345.5)<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">See also <a href="https://github.com/mclements/microsimulation/blob/master/src/rcpp_table.h">
https://github.com/mclements/microsimulation/blob/master/src/rcpp_table.h</a> for an extension to higher dimensions.]<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">Sincerely, Mark.<o:p></o:p></p>
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