12_test_coded_netsdf.cpp

This is an example of how to use the netdem library.

#include "general_net.hpp"
#include "mlpack_utils.hpp"
#include "regression_net.hpp"
#include "utils_math.hpp"
 
using namespace netdem;
using namespace std;
 
void TestCodedNetSDF() {
  // imporat the name list of templates
  vector<string> template_names;
  ifstream file("template_dict.txt");
  if (file.is_open()) {
    string line;
    while (getline(file, line)) {
      template_names.push_back(line);
    }
    file.close();
  } else {
    cout << "file template_dict.txt not exist" << endl;
    return;
  }
  int num_templates = template_names.size();
 
  // notes: rows represent features, columns represent data points.
  vector<arma::mat> dataset(num_templates);
  for (int i = 0; i < template_names.size(); i++) {
    bool loadedDataset = mlpack::data::Load(
        template_names[i] + "/dataset_SDF.txt", dataset[i], true);
    if (!loadedDataset) {
      cout << "loading data erros ..." << endl;
      return;
    }
    cout << template_names[i] << ": " << dataset[i].n_cols << " samples"
         << endl;
  }
  cout << "finished loading data ..." << endl;
 
  // loading latent code
  arma::mat latent_code;
  mlpack::data::Load("latent_code.txt", latent_code, false, false);
  int num_latent_code = latent_code.n_cols;
 
  // loading ann model
  RegressionNet model;
  model.Load("ann_SDF.xml", "SDF");
  cout << "finished loading ann model ..." << endl;
 
  // loop over all templates
  for (int ii = 0; ii < num_templates; ii++) {
    arma::mat test_data = dataset[ii];
 
    int num_x{3}, num_y{1};
    arma::mat test_x = test_data.rows(0, num_x - 1);
    arma::mat test_y = test_data.row(num_x);
    cout << "finished preparing testing data ..." << endl;
 
    arma::mat test_x_coded(num_latent_code + test_x.n_rows, test_x.n_cols);
    for (int i = 0; i < num_latent_code; i++) {
      for (int j = 0; j < test_x.n_cols; j++) {
        test_x_coded(i, j) = latent_code(ii, i);
      }
    }
    for (int i = num_latent_code; i < test_x_coded.n_rows; i++) {
      for (int j = 0; j < test_x.n_cols; j++) {
        test_x_coded(i, j) = test_x(i - num_latent_code, j);
      }
    }
    cout << "finished combining latent code ..." << endl;
 
    auto pred_y = model.Predict(test_x_coded);
    double test_accuracy = MLPackUtils::GetMAE(pred_y, test_y);
    cout << "test mae: " << test_accuracy << endl;
 
    arma::mat joined_yy = std::move(arma::join_cols(pred_y, test_y));
    mlpack::data::Save(template_names[ii] + "/pred_vs_true_SDF.txt", joined_yy,
                       false, true, mlpack::data::FileType::CSVASCII);
  }
}