Point Cloud Library (PCL)  1.3.1
random_sample.hpp
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00001 /*
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00034  * $Id: random_sample.hpp 3029 2011-11-01 04:12:25Z svn $
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00037 
00038 #ifndef PCL_FILTERS_IMPL_RANDOM_SAMPLE_H_
00039 #define PCL_FILTERS_IMPL_RANDOM_SAMPLE_H_
00040 
00041 #include "pcl/filters/random_sample.h"
00042 
00044 template<typename PointT> void
00045 pcl::RandomSample<PointT>::applyFilter (PointCloud &output)
00046 {
00047   // If sample size is 0 or if the sample size is greater then input cloud size
00048   //   then return entire copy of cloud
00049   if (sample_ >= input_->size ())
00050   {
00051     output = *input_;
00052   }
00053   else
00054   {
00055     // Resize output cloud to sample size
00056     output.points.resize (sample_);
00057     output.width = sample_;
00058     output.height = 1;
00059 
00060     // Fill output cloud with first sample points from input cloud
00061     for (size_t i = 0; i < output.size (); ++i)
00062       output.points[i] = input_->points[i];
00063 
00064     // Set random seed so derived indices are the same each time the filter runs
00065     std::srand (seed_);
00066 
00067     // Iterate over the rest of the points of the input cloud picking a random
00068     //   index from the output indices to replace
00069     for (size_t i = output.size (); i < input_->size (); ++i)
00070     {
00071       size_t index = std::rand () % (i + 1);
00072       if (index < output.size ())
00073         output.points[index] = input_->points[i];
00074     }
00075   }
00076 }
00077 
00079 template<typename PointT>
00080 void
00081 pcl::RandomSample<PointT>::applyFilter (std::vector<int> &indices)
00082 {
00083   // If sample size is 0 or if the sample size is greater then input cloud size
00084   //   then return all indices
00085   if (sample_ >= input_->size ())
00086   {
00087     indices = *indices_;
00088   }
00089   else
00090   {
00091     // Resize output indices to sample size
00092     indices.resize (sample_);
00093 
00094     // Fill output indices with first sample indices from input cloud
00095     for (size_t i = 0; i < indices.size (); ++i)
00096       indices[i] = (*indices_)[i];
00097 
00098     // Set random seed so derived indices are the same each time the filter runs
00099     std::srand (seed_);
00100 
00101     // Iterate over the rest of the indices of the input cloud picking a random
00102     //   index from the output indices to replace
00103     for (size_t i = indices.size (); i < (*indices_).size (); ++i)
00104     {
00105       size_t index = std::rand () % (i + 1);
00106       if (index < indices.size ())
00107         indices[index] = (*indices_)[i];
00108     }
00109   }
00110 }
00111 
00112 #define PCL_INSTANTIATE_RandomSample(T) template class PCL_EXPORTS pcl::RandomSample<T>;
00113 
00114 #endif    // PCL_FILTERS_IMPL_RANDOM_SAMPLE_H_
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