In the Dlib library, Sammon mapping is implemented with the Dlib::sammon_projection type. We need to create an instance of this type and then use it as a functional object. Functional object call arguments are the data that we need to transform and the number of dimensions of the new feature space. The input data should be in the form of the std::vector of the single samples of the Dlib::matrix type. All samples should have the same number of dimensions. The result of using this functional object is a new vector of samples with a reduced number of dimensions:

 void SammonReduction(const std::vector<Matrix> &data, long target_dim) {
   Dlib::sammon_projection sp;
   auto new_data = sp(data, target_dim);
 
   for (size_t r = 0; r < new_data.size(); ++r) {
     Matrix vec = new_data[r];
     double x = vec(0, 0);
     double y = vec(1, 0);
   }
 }

The following graph shows the result of using this dimensionality reduction algorithm: