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#ifndef PCL_REGISTRATION_TRANSFORMATION_VALIDATION_EUCLIDEAN_IMPL_H_
#define PCL_REGISTRATION_TRANSFORMATION_VALIDATION_EUCLIDEAN_IMPL_H_

namespace pcl {

namespace registration {

template <typename PointSource, typename PointTarget, typename Scalar>
double
TransformationValidationEuclidean<PointSource, PointTarget, Scalar>::
    validateTransformation(const PointCloudSourceConstPtr& cloud_src,
                           const PointCloudTargetConstPtr& cloud_tgt,
                           const Matrix4& transformation_matrix) const
{
  double fitness_score = 0.0;

  // Transform the input dataset using the final transformation
  pcl::PointCloud<PointSource> input_transformed;
  // transformPointCloud (*cloud_src, input_transformed, transformation_matrix);
  input_transformed.resize(cloud_src->size());
  for (std::size_t i = 0; i < cloud_src->size(); ++i) {
    const PointSource& src = (*cloud_src)[i];
    PointTarget& tgt = input_transformed[i];
    tgt.x = static_cast<float>(
        transformation_matrix(0, 0) * src.x + transformation_matrix(0, 1) * src.y +
        transformation_matrix(0, 2) * src.z + transformation_matrix(0, 3));
    tgt.y = static_cast<float>(
        transformation_matrix(1, 0) * src.x + transformation_matrix(1, 1) * src.y +
        transformation_matrix(1, 2) * src.z + transformation_matrix(1, 3));
    tgt.z = static_cast<float>(
        transformation_matrix(2, 0) * src.x + transformation_matrix(2, 1) * src.y +
        transformation_matrix(2, 2) * src.z + transformation_matrix(2, 3));
  }

  typename MyPointRepresentation::ConstPtr point_rep(new MyPointRepresentation);
  if (!force_no_recompute_) {
    tree_->setPointRepresentation(point_rep);
    tree_->setInputCloud(cloud_tgt);
  }

  pcl::Indices nn_indices(1);
  std::vector<float> nn_dists(1);

  // For each point in the source dataset
  int nr = 0;
  for (const auto& point : input_transformed) {
    // Find its nearest neighbor in the target
    tree_->nearestKSearch(point, 1, nn_indices, nn_dists);

    // Deal with occlusions (incomplete targets)
    if (nn_dists[0] > max_range_)
      continue;

    // Calculate the fitness score
    fitness_score += nn_dists[0];
    ++nr;
  }

  if (nr > 0)
    return (fitness_score / nr);
  return (std::numeric_limits<double>::max());
}

} // namespace registration
} // namespace pcl

#endif // PCL_REGISTRATION_TRANSFORMATION_VALIDATION_EUCLIDEAN_IMPL_H_
