Rcpp gamma integral - r

Question

I am trying to rewrite into (R)cpp an original R function that makes use of the gamma function (from double input). Below the original source. When comping with sourceCpp the following error is raised "no matching function for call to 'gamma(Rcpp::traits::storage_type(<14>:.type)'"
The gamma function should has been put within sugar (as the mean below use) so I expect there should be easily called.
#include <Rcpp.h>
#include <math.h>
using namespace Rcpp;
// original R function
// function (y_pred, y_true)
// {
// eps <- 1e-15
// y_pred <- pmax(y_pred, eps)
// Poisson_LogLoss <- mean(log(gamma(y_true + 1)) + y_pred -
// log(y_pred) * y_true)
// return(Poisson_LogLoss)
// }
// [[Rcpp::export]]
double poissonLogLoss(NumericVector predicted, NumericVector actual) {
NumericVector temp, y_pred_new;
double out;
const double eps=1e-15;
y_pred_new=pmax(predicted,eps);
long n = predicted.size();
for (long i = 0; i < n; ++i) {
temp[i] = log( gamma(actual[i]+1)+y_pred_new[i]-log(y_pred_new[i])*actual[i]);
}
out=mean(temp); // using sugar implementation
return out;
}

Answer 1

You are making this too complicated as the point of Rcpp Sugar is work vectorized. So the following compiles as well:
#include <Rcpp.h>
#include <math.h>
using namespace Rcpp;
// [[Rcpp::export]]
double poissonLogLoss(NumericVector predicted, NumericVector actual) {
NumericVector temp, y_pred_new;
double out;
const double eps=1e-15;
y_pred_new=pmax(predicted,eps);
temp = log(gamma(actual + 1)) + y_pred_new - log(y_pred_new)*actual;
out=mean(temp); // using sugar implementation
return out;
}
Now, you didn't supply any test data so I do not know if this computes correctly or not. Also, because your R expression is already vectorized, this will not be much faster.
Lastly, your compile error is likely due to the Sugar function gamma() expecting an Rcpp object whereas you provided a double.