new_contents: from sklearn import svm
  from sklearn.datasets import load_iris
  
  from onl.nok.sklearn.Porter import port
  
  iris = load_iris()
  clf = svm.LinearSVC(C=1., random_state=0)
  clf.fit(iris.data, iris.target)
  
  # Cheese!
  
  print(port(clf, language='c'))
  
  """
  #include <stdio.h>
  #include <math.h>
  
  int predict (float atts[4]) {
  
      double coefs[3][4] = {{0.18424209458473811, 0.45123000025163923, -0.80794587716737576, -0.45071660033253858}, {0.052877455748516447, -0.89214995228605254, 0.40398084459610972, -0.9376821661447452}, {-0.85070784319293802, -0.98670214922204336, 1.381010448739191, 1.8654095662423917}};
      double inters[3] = {0.10956266406702335, 1.6636707776739579, -1.7096109416521363};
  
      double class_val = -INFINITY;
      int class_idx = -1;
      for (int i = 0; i < 3; i++) {
          double prob = 0.;
          for (int j = 0; j < 4; j++) {
              prob += coefs[i][j] * atts[j];
          }
          if (prob + inters[i] > class_val) {
              class_val = prob + inters[i];
              class_idx = i;
          }
      }
      return class_idx;
  }
  
  int main(int argc, const char * argv[]) {
      float test[4] = {1.f, 2.f, 3.f, 4.f};
      printf("Result: %d\\n", predict(test));
      return 0;
  }
  """
subject: add c example