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 * $Id: random_sample.hpp 5026 2012-03-12 02:51:44Z rusu $
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#ifndef PCL_FILTERS_IMPL_RANDOM_SAMPLE_H_
#define PCL_FILTERS_IMPL_RANDOM_SAMPLE_H_

#include <pcl/filters/random_sample.h>


///////////////////////////////////////////////////////////////////////////////
template<typename PointT> void
pcl::RandomSample<PointT>::applyFilter (PointCloud &output)
{
  unsigned N = static_cast<unsigned> (input_->size ());
  float one_over_N = 1.0f / float (N);

  // If sample size is 0 or if the sample size is greater then input cloud size
  //   then return entire copy of cloud
  if (sample_ >= N)
  {
    output = *input_;
  }
  else
  {
    // Resize output cloud to sample size
    output.points.resize (sample_);
    output.width = sample_;
    output.height = 1;

    // Set random seed so derived indices are the same each time the filter runs
    std::srand (seed_);

    unsigned top = N - sample_;
    unsigned i = 0;
    unsigned index = 0;

    // Algorithm A
    for (size_t n = sample_; n >= 2; n--)
    {
      unsigned int V = unifRand ();
      unsigned S = 0;
      float quot = float (top) * one_over_N;
      while (quot > V)
      {
        S++;
        top--;
        N--;
        quot = quot * float (top) * one_over_N;
      }
      index += S;
      output.points[i++] = input_->points[index++];
      N--;
    }

    index += N * static_cast<unsigned> (unifRand ());
    output.points[i++] = input_->points[index++];
  }
}

///////////////////////////////////////////////////////////////////////////////
template<typename PointT>
void
pcl::RandomSample<PointT>::applyFilter (std::vector<int> &indices)
{
  unsigned N = static_cast<unsigned> (input_->size ());
  float one_over_N = 1.0f / float (N);

  // If sample size is 0 or if the sample size is greater then input cloud size
  //   then return all indices
  if (sample_ >= N)
  {
    indices = *indices_;
  }
  else
  {
    // Resize output indices to sample size
    indices.resize (sample_);

    // Set random seed so derived indices are the same each time the filter runs
    std::srand (seed_);

    // Algorithm A
    unsigned top = N - sample_;
    unsigned i = 0;
    unsigned index = 0;

    for (size_t n = sample_; n >= 2; n--)
    {
      unsigned int V = unifRand ();
      unsigned S = 0;
      float quot = float (top) * one_over_N;
      while (quot > V)
      {
        S++;
        top--;
        N--;
        quot = quot * float (top) * one_over_N;
      }
      index += S;
      indices[i++] = (*indices_)[index++];
      N--;
    }

    index += N * static_cast<unsigned> (unifRand ());
    indices[i++] = (*indices_)[index++];
  }
}

#define PCL_INSTANTIATE_RandomSample(T) template class PCL_EXPORTS pcl::RandomSample<T>;

#endif    // PCL_FILTERS_IMPL_RANDOM_SAMPLE_H_
